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(T4 + RTX 2070)","ttft_ms":85.0,"warm_latency_ms":1015.8,"tokens_per_sec":71.87,"http_status":200,"hivemind_quality_score":76.5,"frontier_llm_name":"GPT-4o-mini / Claude Haiku 3.5","frontier_quality_score":84.0,"frontier_latency_ms":1450.0,"frontier_cost_usd_per_1m":0.6,"daily_usage_sufficiency_pct":89.0,"verdict_badge":"⚡ 1.4x FASTER • 89% DAILY COVERAGE","use_case_fr":"Triage d'intentions ultra-rapide, classification JSON, micro-agents (< 1,0s)","use_case_en":"Ultra-fast intent triage, JSON classification & micro-agents (< 1.0s)","use_case_es":"Clasificación rápida de intenciones, JSON y microagentes (< 1.0s)","use_case_de":"Ultraschnelle Intent-Klassifizierung, JSON & Mikro-Agenten (< 1,0s)","use_case_zh":"超快速意图分类、JSON格式化与微代理 (< 1.0秒)","honest_comparison_fr":"Moins profond sur le raisonnement abstrait (-7,5 pts vs Haiku), mais à 71,9 tok/s (1,01s), il couvre 89% des besoins de routage, résumé court et extraction JSON à coût zéro.","honest_comparison_en":"Lower abstract reasoning depth (-7.5 pts vs Haiku), but at 71.9 tok/s (1.01s) it satisfies 89% of routing, short summarization, and JSON extraction tasks at zero cash cost.","prompt_tested":"Summarize in 2 crisp bullet points why decentralized consumer GPUs democratize AI inference.","response_excerpt":"• Decentralized consumer GPUs aggregate idle worldwide hardware into a shared pool, eliminating cloud monopolies.\n• Contributors earn reciprocal compute rights (HMT) to run open models locally and via API at zero cash cost.","recommended_temp":0.3,"recommended_max_tokens":256},{"bee_index":2,"model_id":"hivemind/coder-lite","category":"fast_dense","architecture":"3.1B Dense Qwen2.5-Coder-3B-Instruct (Q4_K_M)","active_params_b":3.1,"total_params_b":3.1,"vram_footprint_gb":2.7,"gpu_residency":"100% GPU (T4 + RTX 2070)","ttft_ms":110.0,"warm_latency_ms":1508.6,"tokens_per_sec":53.03,"http_status":200,"hivemind_quality_score":81.2,"frontier_llm_name":"GPT-4o / Copilot Autocomplete","frontier_quality_score":88.5,"frontier_latency_ms":1950.0,"frontier_cost_usd_per_1m":2.5,"daily_usage_sufficiency_pct":92.0,"verdict_badge":"⚡ 53 TOK/S • 92% AUTOCOMPLETE FIT","use_case_fr":"Autocomplétion IDE inline, regex, commandes Git/Bash & petites fonctions (< 1,5s)","use_case_en":"Inline IDE autocomplete, regex, Git/Bash one-liners & small functions (< 1.5s)","use_case_es":"Autocompletado IDE en línea, regex, comandos Git/Bash y funciones breves (< 1.5s)","use_case_de":"Inline-IDE-Autovervollständigung, Regex, Git/Bash-Befehle (< 1,5s)","use_case_zh":"IDE内联代码补全、正则表达式、Git/Shell单行命令 (< 1.5秒)","honest_comparison_fr":"Moins adapté à l'architecture de 10 fichiers (-7,3 pts vs GPT-4o), mais 29% plus rapide (1,5s) et parfait pour 92% des complétions de code quotidiennes dans VS Code / Zed.","honest_comparison_en":"Less suited for 10-file architecture (-7.3 pts vs GPT-4o), but 29% faster (1.5s) and ideal for 92% of everyday inline code completions in VS Code / Zed.","prompt_tested":"Write a compact Python function `clamp(val, lo, hi)` with type hints and a 1-line docstring.","response_excerpt":"def clamp(val: float, lo: float, hi: float) -> float:\n    \"\"\"Clamp val to the closed interval [lo, hi].\"\"\"\n    return max(lo, min(val, hi))","recommended_temp":0.1,"recommended_max_tokens":256},{"bee_index":3,"model_id":"hivemind/gemma-core","category":"core_multilingual","architecture":"4.3B Dense Google Gemma 3 4B-IT (Multilingual & Multimodal Core)","active_params_b":4.3,"total_params_b":4.3,"vram_footprint_gb":3.8,"gpu_residency":"100% GPU (T4 + RTX 2070)","ttft_ms":145.0,"warm_latency_ms":2082.1,"tokens_per_sec":36.98,"http_status":200,"hivemind_quality_score":84.8,"frontier_llm_name":"Gemini 2.5 Flash / GPT-4o","frontier_quality_score":90.5,"frontier_latency_ms":2450.0,"frontier_cost_usd_per_1m":1.25,"daily_usage_sufficiency_pct":93.5,"verdict_badge":"🌍 93.5% MULTILINGUAL COVERAGE","use_case_fr":"Rédaction technique multilingue (FR/EN/ES/DE/ZH), synthèse doc & JSON structuré","use_case_en":"Multilingual technical writing (FR/EN/ES/DE/ZH), doc synthesis & structured JSON","use_case_es":"Redacción técnica multilingüe (FR/EN/ES/DE/ZH), síntesis y JSON estructurado","use_case_de":"Mehrsprachige technische Dokumentation (FR/EN/ES/DE/ZH) & strukturiertes JSON","use_case_zh":"多语言技术写作 (法/英/西/德/中)、文档总结与结构化JSON","honest_comparison_fr":"Légèrement derrière Gemini 2.5 Pro sur les textes littéraires longs (-5,7 pts), mais couvre 93,5% des besoins de rédaction technique, traduction et documentation développeur en 2,08s.","honest_comparison_en":"Slightly behind Gemini 2.5 Pro on long literary essays (-5.7 pts), but covers 93.5% of technical writing, translation, and developer documentation needs in 2.08s.","prompt_tested":"Explique en 2 phrases claires comment fonctionne la réciprocité de calcul non-monétaire HMT dans La Ruche.","response_excerpt":"Dans La Ruche HiveMind, chaque citoyen qui partage les cycles de veille de son GPU gagne des points de réflexion HMT proportionnels au travail vérifié. Ces points permettent ensuite d'interroger gratuitement tous les modèles de code et de science de l'essaim.","recommended_temp":0.4,"recommended_max_tokens":512},{"bee_index":4,"model_id":"hivemind/mistral-core","category":"core_multilingual","architecture":"7.2B Dense Mistral 7B Instruct v0.3 (European FR/EN Core)","active_params_b":7.2,"total_params_b":7.2,"vram_footprint_gb":4.9,"gpu_residency":"100% GPU (T4 + RTX 2070)","ttft_ms":160.0,"warm_latency_ms":2390.5,"tokens_per_sec":33.47,"http_status":200,"hivemind_quality_score":85.4,"frontier_llm_name":"Mistral Large 2 / GPT-4o","frontier_quality_score":91.0,"frontier_latency_ms":2900.0,"frontier_cost_usd_per_1m":6.0,"daily_usage_sufficiency_pct":91.8,"verdict_badge":"🇪🇺 SOVEREIGN FR/EN • 33.5 TOK/S","use_case_fr":"Synthèse exécutive européenne, gouvernance AGPL-3.0, e-mails & support client","use_case_en":"European executive synthesis, AGPL-3.0 governance, emails & user support","use_case_es":"Síntesis ejecutiva europea, gobernanza AGPL-3.0 y soporte al usuario","use_case_de":"Europäische Zusammenfassungen, AGPL-3.0-Governance & Support","use_case_zh":"欧洲双语技术摘要、开源治理文档与客户支持","honest_comparison_fr":"5,6 pts sous Mistral Large 2 sur le droit complexe, mais 100% souverain, 33,5 tok/s, et suffisant pour 91,8% des tâches de rédaction, synthèse et support bilingue.","honest_comparison_en":"5.6 pts below Mistral Large 2 on complex legal edge cases, yet 100% sovereign, 33.5 tok/s, and sufficient for 91.8% of bilingual drafting and summarization tasks.","prompt_tested":"Give 3 concise advantages of open-weights Mixture-of-Experts models over closed proprietary APIs.","response_excerpt":"1. Cost Efficiency: Sparse MoEs activate only a fraction of parameters per token, cutting compute cost.\n2. Data Privacy: Weights run on sovereign hardware with zero telemetry leakage.\n3. Domain Specialization: Modular LoRA experts can be fine-tuned independently.","recommended_temp":0.4,"recommended_max_tokens":512},{"bee_index":5,"model_id":"hivemind/coder","category":"fast_dense","architecture":"7.6B Dense Qwen2.5-Coder-7B-Instruct (Pinned Hot in VRAM)","active_params_b":7.6,"total_params_b":7.6,"vram_footprint_gb":5.2,"gpu_residency":"100% GPU (Pinned Hot on T4 + RTX 2070 + RTX 4070)","ttft_ms":135.0,"warm_latency_ms":2929.8,"tokens_per_sec":32.77,"http_status":200,"hivemind_quality_score":88.4,"frontier_llm_name":"Claude 3.7/4.5 Sonnet / GPT-4o","frontier_quality_score":93.2,"frontier_latency_ms":3850.0,"frontier_cost_usd_per_1m":9.0,"daily_usage_sufficiency_pct":94.0,"verdict_badge":"💻 #1 MOST USED BEE • 94% IDE FIT","use_case_fr":"Développement quotidien Python/TS/Rust/SQL, tests pytest, refactoring IDE (Continue/Cline)","use_case_en":"Everyday Python/TS/Rust/SQL coding, pytest suites & IDE refactoring (Continue/Cline)","use_case_es":"Programación diaria Python/TS/Rust/SQL, pruebas pytest y refactorización en IDE","use_case_de":"Tägliche Python/TS/Rust/SQL-Entwicklung, Pytest-Tests & IDE-Refactoring","use_case_zh":"日常 Python/TS/Rust/SQL 开发、单元测试与 IDE 重构","honest_comparison_fr":"À seulement 4,8 pts de Claude Sonnet sur HumanEval/MBPP, mais 24% plus rapide (2,93s, 0s cold start) et couvre 94% des tâches de programmation quotidiennes gratuitement.","honest_comparison_en":"Within 4.8 pts of Claude Sonnet on HumanEval/MBPP, while 24% faster (2.93s, 0s cold start) and covering 94% of daily coding tasks for free.","prompt_tested":"Write a Python function `binary_search(arr: list[int], target: int) -> int` returning the index or -1.","response_excerpt":"def binary_search(arr: list[int], target: int) -> int:\n    lo, hi = 0, len(arr) - 1\n    while lo <= hi:\n        mid = (lo + hi) // 2\n        if arr[mid] == target: return mid\n        elif arr[mid] < target: lo = mid + 1\n        else: hi = mid - 1\n    return -1","recommended_temp":0.15,"recommended_max_tokens":768},{"bee_index":6,"model_id":"hivemind/qwen35-core","category":"fast_dense","architecture":"8.2B Dense Qwen 3.5 8B Hybrid Thinking & Polyglot Core","active_params_b":8.2,"total_params_b":8.2,"vram_footprint_gb":7.4,"gpu_residency":"100% GPU (T4 16 GB + RTX 4070 12 GB)","ttft_ms":175.0,"warm_latency_ms":3664.2,"tokens_per_sec":30.02,"http_status":200,"hivemind_quality_score":89.1,"frontier_llm_name":"OpenAI o3-mini / Claude Sonnet 4.5","frontier_quality_score":93.8,"frontier_latency_ms":5400.0,"frontier_cost_usd_per_1m":4.4,"daily_usage_sufficiency_pct":93.2,"verdict_badge":"🧠 HYBRID THINKING • 1.5x FASTER THAN o3-MINI","use_case_fr":"Rust système sans allocation, C++20, invariants mémoire & raisonnement étape par étape","use_case_en":"Zero-allocation Rust, C++20, memory invariants & step-by-step hybrid reasoning","use_case_es":"Rust sin asignaciones, C++20, invariantes de memoria y razonamiento paso a paso","use_case_de":"Zero-Allocation Rust, C++20, Speicherinvarianten & schrittweises Denken","use_case_zh":"零分配 Rust、C++20、内存不变量与混合逐步推理","honest_comparison_fr":"4,7 pts sous o3-mini sur les puzzles algorithmiques extrêmes, mais 1,5x plus rapide (3,66s vs 5,4s) et résout 93,2% des problèmes de typage Rust/C++ et d'architecture.","honest_comparison_en":"4.7 pts below o3-mini on extreme competition puzzles, yet 1.5x faster (3.66s vs 5.4s) and solves 93.2% of Rust/C++ ownership and systems design problems.","prompt_tested":"Write a zero-allocation Rust function `fn gcd(mut a: u64, mut b: u64) -> u64` using Euclid's algorithm.","response_excerpt":"pub const fn gcd(mut a: u64, mut b: u64) -> u64 {\n    while b != 0 {\n        let t = b;\n        b = a % b;\n        a = t;\n    }\n    a\n}","recommended_temp":0.2,"recommended_max_tokens":768},{"bee_index":7,"model_id":"hivemind/bee-stars","category":"scientific_specialist","architecture":"7.6B Astrophysics & Symplectic N-Body Specialist Bee (Pinned :8294)","active_params_b":7.6,"total_params_b":7.6,"vram_footprint_gb":5.4,"gpu_residency":"100% GPU (Pinned Dedicated Port :8294 • 0.0s Cold Load)","ttft_ms":120.0,"warm_latency_ms":3441.5,"tokens_per_sec":27.89,"http_status":200,"hivemind_quality_score":96.4,"frontier_llm_name":"GPT-4o / Claude Sonnet 4.5 (Ungrounded)","frontier_quality_score":78.5,"frontier_latency_ms":4100.0,"frontier_cost_usd_per_1m":10.0,"daily_usage_sufficiency_pct":98.5,"verdict_badge":"🏆 BEATS FRONTIER LLMs (+17.9 PTS IN ASTRO)","use_case_fr":"Astrophysique, transits Kepler/TESS (BLS), mécanique orbitale symplectique & relativité","use_case_en":"Astrophysics, Kepler/TESS transits (BLS), symplectic orbital mechanics & GR","use_case_es":"Astrofísica, tránsitos Kepler/TESS (BLS), mecánica orbital simpléctica y RG","use_case_de":"Astrophysik, Kepler/TESS-Transite (BLS), symplektische Himmelsmechanik & ART","use_case_zh":"天体物理学、开普勒/TESS凌日 (BLS)、辛轨道力学与广义相对论","honest_comparison_fr":"Surpasse les LLM généralistes (+17,9 pts) grâce à son entraînement QLoRA dédié et au couplage avec le repliement CUDA PTX BLS et les intégrateurs symplectiques Yoshida.","honest_comparison_en":"Outperforms generalist frontier LLMs (+17.9 pts) thanks to domain QLoRA training coupled with CUDA PTX BLS transit folding and Yoshida symplectic integrators.","prompt_tested":"State the 2nd-order symplectic leapfrog kick-drift-kick update equations for a gravitational N-body system.","response_excerpt":"1. Half-kick: v_{i+1/2} = v_i + (Δt / 2) a(x_i)\n2. Full-drift: x_{i+1} = x_i + Δt v_{i+1/2}\n3. Half-kick: v_{i+1} = v_{i+1/2} + (Δt / 2) a(x_{i+1}) — preserving phase-space volume and bounding |ΔH/H_0|.","recommended_temp":0.2,"recommended_max_tokens":768},{"bee_index":8,"model_id":"hivemind/bee-rusty-sundials","category":"scientific_specialist","architecture":"7.6B Scientific Bee + Deterministic Rust CVODE/ARKODE/IDA Solver Gate","active_params_b":7.6,"total_params_b":7.6,"vram_footprint_gb":5.6,"gpu_residency":"100% GPU + Deterministic CPU/GPU Solver Verification","ttft_ms":95.0,"warm_latency_ms":2887.0,"tokens_per_sec":33.25,"http_status":200,"hivemind_quality_score":100.0,"frontier_llm_name":"GPT-4o / Claude Opus 4.6 (Text-Only ODE)","frontier_quality_score":64.0,"frontier_latency_ms":4600.0,"frontier_cost_usd_per_1m":15.0,"daily_usage_sufficiency_pct":100.0,"verdict_badge":"🏆 100% INVARIANT EXACTNESS (+36 PTS VS LLM)","use_case_fr":"EDO/EDP raides (Robertson, Navier-Stokes, Gross-Pitaevskii, Hopfield) avec garantie d'invariants","use_case_en":"Stiff ODE/PDEs (Robertson, Navier-Stokes, Gross-Pitaevskii, Hopfield) with invariant guarantees","use_case_es":"EDO/EDP rígidas (Robertson, Navier-Stokes, Gross-Pitaevskii) con garantía de invariantes","use_case_de":"Steife DGL/PDGL (Robertson, Navier-Stokes, Gross-Pitaevskii) mit Invariantengarantie","use_case_zh":"刚性常/偏微分方程 (Robertson, 纳维-斯托克斯, 量子流体) 守恒律100%验证","honest_comparison_fr":"Les LLM généralistes hallucinent les trajectoires numériques raides (64%). Couplée à POST /v1/hivemind/bees/rusty-sundials/rescue (200 ms), cette abeille garantit 100% de conservation (|Δm| < 10^-14).","honest_comparison_en":"Pure-text frontier LLMs hallucinate stiff numerical trajectories (64%). Coupled with POST /v1/hivemind/bees/rusty-sundials/rescue (200 ms), this Bee guarantees 100% conservation (|Δm| < 10^-14).","prompt_tested":"Explain why explicit Euler blows up on the stiff Robertson chemical kinetics ODE (k2=3e7) and how CVODE BDF rescues it.","response_excerpt":"Explicit Euler is stability-limited by |1 + h λ_max| <= 1, requiring h < 6.6e-8 s for λ ≈ -3e7 (causing negative concentrations). rusty-SUNDIALS CVODE BDF uses L-stable implicit backward differentiation with Newton-Krylov iteration, preserving positivity and exact mass conservation y1 + y2 + y3 = 1.","recommended_temp":0.15,"recommended_max_tokens":768},{"bee_index":9,"model_id":"hivemind/bee-lean-prover","category":"scientific_specialist","architecture":"8.0B Goedel-Prover-V2-8B (Q6_K High-Precision) + Lean 4 Formal Verifier","active_params_b":8.0,"total_params_b":8.0,"vram_footprint_gb":8.7,"gpu_residency":"100% GPU (8.7 GB Q6_K on T4 16 GB / RTX 4070 12 GB)","ttft_ms":210.0,"warm_latency_ms":4839.7,"tokens_per_sec":16.53,"http_status":200,"hivemind_quality_score":95.8,"frontier_llm_name":"Claude Sonnet 4.5 / GPT-4o (Lean 4 Zero-Shot)","frontier_quality_score":76.0,"frontier_latency_ms":5200.0,"frontier_cost_usd_per_1m":9.0,"daily_usage_sufficiency_pct":97.0,"verdict_badge":"🏆 +19.8 PTS LEAN 4 PROOF SOUNDNESS","use_case_fr":"Preuves formelles Lean 4 / Mathlib4 vérifiées par compilateur avec zéro 'sorry'","use_case_en":"Compiler-verified Lean 4 / Mathlib4 formal theorem proving with zero 'sorry'","use_case_es":"Demostración formal de teoremas en Lean 4 / Mathlib4 sin 'sorry'","use_case_de":"Formale Theorembeweise in Lean 4 / Mathlib4 ohne 'sorry'","use_case_zh":"Lean 4 / Mathlib4 零 sorry 机器验证形式化定理证明","honest_comparison_fr":"Plus spécialisée que GPT-4o (+19,8 pts sur Lean 4 Mathlib4 sans sorry) grâce aux poids Goedel-Prover-V2 quantifiés en Q6_K haute précision.","honest_comparison_en":"Outperforms general GPT-4o by +19.8 pts on zero-sorry Lean 4 Mathlib4 proofs thanks to high-precision Q6_K Goedel-Prover-V2 weights.","prompt_tested":"Write a valid Lean 4 theorem proving that addition of natural numbers is commutative using ` Nat.add_comm`.","response_excerpt":"import Mathlib\n\ntheorem nat_add_symm (a b : ℕ) : a + b = b + a := by\n  exact Nat.add_comm a b","recommended_temp":0.1,"recommended_max_tokens":768},{"bee_index":10,"model_id":"hivemind/coder-plus","category":"fast_dense","architecture":"14.8B Dense Qwen2.5-Coder-14B / DeepSeek-R1-14B","active_params_b":14.8,"total_params_b":14.8,"vram_footprint_gb":9.8,"gpu_residency":"55% GPU / 45% CPU or 100% GPU on 16 GB T4","ttft_ms":420.0,"warm_latency_ms":27980.0,"tokens_per_sec":3.93,"http_status":200,"hivemind_quality_score":89.5,"frontier_llm_name":"Claude Sonnet 4.5 / DeepSeek-V3","frontier_quality_score":94.0,"frontier_latency_ms":6500.0,"frontier_cost_usd_per_1m":9.0,"daily_usage_sufficiency_pct":91.0,"verdict_badge":"🐢 DENSE 14B BASELINE (USE SPARSE MoE INSTEAD)","use_case_fr":"Référence dense 14B pour le refactoring profond hors-ligne (préférez nos MoE 20B 1,83x plus rapides)","use_case_en":"Dense 14B reference for deep offline refactoring (prefer our 1.83x faster 20B Sparse MoEs)","use_case_es":"Referencia densa 14B para refactorización profunda (prefiera nuestros MoE 20B 1.83x más rápidos)","use_case_de":"Dichte 14B-Referenz für tiefes Refactoring (unsere 20B Sparse MoEs sind 1,83x schneller)","use_case_zh":"14B 稠密基准模型（建议使用快 1.83 倍的 20B 稀疏 MoE 蜜蜂）","honest_comparison_fr":"Bonne qualité (89,5%), mais lent en mode dense (3,93 tok/s). C'est précisément pourquoi nos abeilles Sparse MoE 20B et 3-Tome Polyglot MoE ont été créées (jusqu'à 44,6 tok/s).","honest_comparison_en":"Solid quality (89.5%), but slow as a dense 14B model (3.93 tok/s). This is exactly why our 20B Sparse MoEs and 3-Tome Polyglot MoE were engineered (up to 44.6 tok/s).","prompt_tested":"Provide a thread-safe singleton pattern in Python using `__new__` and `threading.Lock`.","response_excerpt":"import threading\n\nclass Singleton:\n    _instance = None\n    _lock = threading.Lock()\n    def __new__(cls):\n        if cls._instance is None:\n            with cls._lock:\n                if cls._instance is None:\n                    cls._instance = super().__new__(cls)\n        return cls._instance","recommended_temp":0.2,"recommended_max_tokens":512},{"bee_index":11,"model_id":"hivemind/bee-ruche-moe","category":"sparse_moe_20b","architecture":"20B Sparse MoE (2.4B Active/Token • Top-2 of 8 Experts • GPT-OSS-20B)","active_params_b":2.4,"total_params_b":20.0,"vram_footprint_gb":14.0,"gpu_residency":"64% GPU / 36% CPU (Sparse Top-2 Gating)","ttft_ms":310.0,"warm_latency_ms":14720.0,"tokens_per_sec":6.79,"http_status":200,"hivemind_quality_score":90.4,"frontier_llm_name":"GPT-4o / Claude Sonnet 4.5","frontier_quality_score":93.8,"frontier_latency_ms":4800.0,"frontier_cost_usd_per_1m":9.0,"daily_usage_sufficiency_pct":93.0,"verdict_badge":"🐝 20B CAPACITY • 1.83x FASTER THAN 14B DENSE","use_case_fr":"Synthèse multi-experts 20B, théorie des jeux (Nash/Kelly) & planification d'architecture","use_case_en":"20B multi-expert synthesis, game theory (Nash/Kelly) & architectural planning","use_case_es":"Síntesis multiexperto 20B, teoría de juegos (Nash/Kelly) y arquitectura","use_case_de":"20B Multi-Experten-Synthese, Spieltheorie (Nash/Kelly) & Architekturplanung","use_case_zh":"20B 稀疏多专家综合推理、博弈论与系统架构规划","honest_comparison_fr":"À seulement 3,4 pts de GPT-4o tout en n'activant que 2,4B paramètres par token (1,83x plus rapide que le 14B dense), couvrant 93% des besoins d'architecture complexe.","honest_comparison_en":"Within 3.4 pts of GPT-4o while activating only 2.4B parameters per token (1.83x faster than 14B dense), covering 93% of complex architectural design tasks.","prompt_tested":"Explain why Top-2 sparse Mixture-of-Experts routing achieves 20B knowledge capacity at 2.4B compute cost.","response_excerpt":"A Top-2 Sparse MoE stores specialized domain knowledge across 8 expert FFN sub-networks (20B total), but the learned softmax gate routes each token to only the 2 highest-scoring experts (2.4B active FLOPs).","recommended_temp":0.3,"recommended_max_tokens":768},{"bee_index":12,"model_id":"hivemind/moe-qwen35-bee","category":"sparse_moe_20b","architecture":"20B Sparse MoE (3.0B Active/Token • Polyglot-Singularity & PDE Expert)","active_params_b":3.0,"total_params_b":20.0,"vram_footprint_gb":14.0,"gpu_residency":"64% GPU / 36% CPU (Sparse Top-2 Gating)","ttft_ms":295.0,"warm_latency_ms":13880.0,"tokens_per_sec":7.2,"http_status":200,"hivemind_quality_score":91.0,"frontier_llm_name":"DeepSeek-R1 / Claude Sonnet 4.5","frontier_quality_score":94.2,"frontier_latency_ms":5900.0,"frontier_cost_usd_per_1m":8.0,"daily_usage_sufficiency_pct":93.8,"verdict_badge":"🐝 93.8% SCIENTIFIC & SYSTEMS COVERAGE","use_case_fr":"Ingénierie polyglotte Rust/CUDA/Python & modélisation physique multi-échelle","use_case_en":"Polyglot Rust/CUDA/Python systems engineering & multi-scale physics modeling","use_case_es":"Ingeniería poliglota Rust/CUDA/Python y modelado físico multiescala","use_case_de":"Polyglottes Rust/CUDA/Python-Systemengineering & Multiskalen-Physik","use_case_zh":"多语言 Rust/CUDA/Python 系统工程与多尺度物理建模","honest_comparison_fr":"À 3,2 pts de DeepSeek-R1 671B sur les preuves longues, mais tourne sur un seul nœud 16 Go et satisfait 93,8% des tâches de calcul scientifique et système.","honest_comparison_en":"Within 3.2 pts of DeepSeek-R1 671B on long derivations, while running on a single 16 GB node and satisfying 93.8% of scientific and systems engineering tasks.","prompt_tested":"Compare Method-of-Lines ARKODE IMEX integration vs explicit RK4 for the viscous Burgers PDE.","response_excerpt":"For the viscous Burgers PDE u_t + u u_x = ν u_xx, explicit RK4 suffers from parabolic stiffness Δt <= O(Δx^2 / ν). ARKODE IMEX treats the stiff diffusion ν u_xx implicitly (L-stable) and nonlinear advection explicitly.","recommended_temp":0.25,"recommended_max_tokens":768},{"bee_index":13,"model_id":"hivemind/moe-general","category":"sparse_moe_20b","architecture":"20B Sparse MoE (3.6B Active/Token • General Reasoning & Synthesis)","active_params_b":3.6,"total_params_b":20.0,"vram_footprint_gb":14.0,"gpu_residency":"64% GPU / 36% CPU (Sparse Top-2 Gating)","ttft_ms":320.0,"warm_latency_ms":15970.0,"tokens_per_sec":6.26,"http_status":200,"hivemind_quality_score":90.1,"frontier_llm_name":"GPT-4o / Gemini 2.5 Pro","frontier_quality_score":93.9,"frontier_latency_ms":4500.0,"frontier_cost_usd_per_1m":10.0,"daily_usage_sufficiency_pct":92.5,"verdict_badge":"🌍 92.5% GENERAL REASONING COVERAGE","use_case_fr":"Analyse stratégique, synthèse interdisciplinaire (bio/droit/économie) & raisonnement long","use_case_en":"Strategic analysis, interdisciplinary synthesis (bio/policy/econ) & long reasoning","use_case_es":"Análisis estratégico, síntesis interdisciplinaria y razonamiento profundo","use_case_de":"Strategische Analyse, interdisziplinäre Synthese & tiefes Denken","use_case_zh":"战略分析、跨学科综合推理（生物/经济/治理）与深度长思考","honest_comparison_fr":"3,8 pts sous GPT-4o sur la culture générale encyclopédique rare, mais couvre 92,5% des besoins d'analyse stratégique, de synthèse de rapports et de raisonnement.","honest_comparison_en":"3.8 pts below GPT-4o on obscure encyclopedic trivia, yet covers 92.5% of strategic analysis, report synthesis, and multi-step reasoning needs.","prompt_tested":"Synthesize the economic difference between speculative crypto-mining and useful BOINC/HiveMind AI compute.","response_excerpt":"Speculative PoW mining burns megawatts on arbitrary SHA-256 hash puzzles with zero intrinsic utility. HiveMind Proof-of-Useful-Work channels consumer GPUs into verified AI inference, LoRA training, and astrophysics simulations, backing every HMT point with real scientific and developer output.","recommended_temp":0.35,"recommended_max_tokens":768},{"bee_index":14,"model_id":"hivemind/moe-coder","category":"sparse_moe_20b","architecture":"30B-A3B Sparse Coding MoE (3.3B Active/Token • Qwen3-Coder-30B-A3B)","active_params_b":3.3,"total_params_b":30.5,"vram_footprint_gb":14.5,"gpu_residency":"64% GPU / 36% CPU (or 100% GPU on 24 GB Nodes)","ttft_ms":305.0,"warm_latency_ms":15120.0,"tokens_per_sec":6.61,"http_status":200,"hivemind_quality_score":91.2,"frontier_llm_name":"Claude Sonnet 4.5 / GPT-4o","frontier_quality_score":94.0,"frontier_latency_ms":4900.0,"frontier_cost_usd_per_1m":9.0,"daily_usage_sufficiency_pct":94.5,"verdict_badge":"💻 30B CODING CAPACITY • 94.5% COVERAGE","use_case_fr":"Architecture logicielle multi-fichiers, refactoring d'agents & revue de code approfondie","use_case_en":"Multi-file software architecture, agentic refactoring & deep code review","use_case_es":"Arquitectura de software multifichero, refactorización agéntica y revisión de código","use_case_de":"Multi-Datei-Softwarearchitektur, Agenten-Refactoring & Code-Review","use_case_zh":"多文件软件架构、代理式重构与深度代码审查","honest_comparison_fr":"À seulement 2,8 pts de Claude Sonnet 4.5, offrant une capacité de 30B paramètres qui couvre 94,5% des tâches d'ingénierie logicielle avancée.","honest_comparison_en":"Within 2.8 pts of Claude Sonnet 4.5, delivering 30B parameter coding capacity that covers 94.5% of advanced software engineering workflows.","prompt_tested":"Design a lock-free token-bucket rate limiter interface in Rust using `AtomicU64` compare_exchange_weak.","response_excerpt":"pub struct AtomicTokenBucket { tokens: AtomicU64, last_ns: AtomicU64 }\nimpl AtomicTokenBucket {\n    pub fn try_acquire(&self, cost: u64) -> bool {\n        self.tokens.fetch_update(Ordering::AcqRel, Ordering::Acquire, |cur| cur.checked_sub(cost)).is_ok()\n    }\n}","recommended_temp":0.15,"recommended_max_tokens":1024},{"bee_index":15,"model_id":"hivemind/auto","category":"fast_dense","architecture":"Smart Residency & Intent Router (Routes to Hot-in-VRAM Specialist Bee)","active_params_b":7.6,"total_params_b":20.0,"vram_footprint_gb":0.0,"gpu_residency":"100% GPU (Selects `loaded_in_vram: true` Producer Automatically)","ttft_ms":115.0,"warm_latency_ms":2450.0,"tokens_per_sec":34.8,"http_status":200,"hivemind_quality_score":90.8,"frontier_llm_name":"OpenRouter Auto / GPT-4o","frontier_quality_score":93.5,"frontier_latency_ms":3600.0,"frontier_cost_usd_per_1m":7.5,"daily_usage_sufficiency_pct":95.0,"verdict_badge":"🧭 ZERO COLD-START • 95% DAILY COVERAGE","use_case_fr":"Point d'entrée universel par défaut : choisit automatiquement la meilleure abeille chaude en VRAM","use_case_en":"Default universal entry point: automatically picks the best bee already hot in VRAM","use_case_es":"Punto de entrada universal: elige automáticamente la mejor abeja caliente en VRAM","use_case_de":"Universeller Standard-Endpunkt: wählt automatisch die beste Bee im VRAM","use_case_zh":"默认智能路由入口：自动选择显存中已热加载的最佳专科蜜蜂","honest_comparison_fr":"Élimine toute hésitation utilisateur : en routant selon la langue et le domaine vers les GPU déjà chauds, hivemind/auto couvre 95% des usages en ~2,4s.","honest_comparison_en":"Eliminates model-picking friction: by routing on language and domain to already-warm GPUs, hivemind/auto covers 95% of daily requests in ~2.4s.","prompt_tested":"Calculate the orbital period ratio of a 2:1 mean-motion exoplanet resonance and state Kepler's third law.","response_excerpt":"The orbital period ratio of a 2:1 mean-motion resonance is 2:1 (the inner planet completes two orbits per outer orbit). By Kepler's third law (P^2 ∝ a^3), their semi-major axes satisfy a_outer / a_inner = 2^(2/3) ≈ 1.5874.","recommended_temp":0.3,"recommended_max_tokens":512},{"bee_index":16,"model_id":"hivemind/moe-coder-polyglot-3tome","category":"multimodal_super_moe","architecture":"30.5B 3-Tome Polyglot Coding MoE (8 Clusters, 16 Bees • Python/C/C++/Rust + PIE Speculative)","active_params_b":3.3,"total_params_b":30.5,"vram_footprint_gb":6.1,"gpu_residency":"100% GPU Hybrid Swarm (T4 16 GB + RTX 4070 12 GB + RTX 2070 8 GB)","ttft_ms":92.0,"warm_latency_ms":1840.2,"tokens_per_sec":44.6,"http_status":200,"hivemind_quality_score":93.1,"frontier_llm_name":"Claude Sonnet 4.5 / Cursor Pro Agent","frontier_quality_score":94.6,"frontier_latency_ms":4200.0,"frontier_cost_usd_per_1m":12.0,"daily_usage_sufficiency_pct":96.5,"verdict_badge":"🚀 96.5% IDE PARITY • 2.3x FASTER VIA PIE","use_case_fr":"Pipeline complet d'ingénierie (Python, C, C++, Rust) : Architecture, Découpage DAG, Code, SIMD/CUDA, Sécurité CWE, Tests & PR Merge","use_case_en":"Full software engineering DAG (Python, C, C++, Rust): Architecture, Task Split, Coding, SIMD/CUDA, CWE Security, Tests & PR Merge","use_case_es":"Pipeline completo de ingeniería (Python, C, C++, Rust): Arquitectura, División DAG, Código, SIMD/CUDA, Seguridad CWE, Tests y PR","use_case_de":"Vollständige Engineering-Pipeline (Python, C, C++, Rust): Architektur, DAG-Split, Code, SIMD/CUDA, CWE-Security, Tests & PR","use_case_zh":"全栈多语言工程管线 (Python/C/C++/Rust)：架构、DAG拆分、编码、SIMD/CUDA优化、CWE安全加固与PR合并","honest_comparison_fr":"Après 3 Tomes d'entraînement nocturne (7 200 shards, perte -99,07%), notre MoE polyglotte atteint 93,1% (à 1,5 pt de Claude Sonnet 4.5), génère à 44,6 tok/s (2,3x plus rapide) et couvre 96,5% des workflows IDE.","honest_comparison_en":"After 3 Tomes of nocturnal training (7,200 shards, -99.07% loss), our polyglot MoE reaches 93.1% (within 1.5 pts of Claude Sonnet 4.5), streams at 44.6 tok/s (2.3x faster), and covers 96.5% of IDE workflows.","prompt_tested":"Split, implement, benchmark, and security-harden a zero-allocation SIMD ring-buffer parser in Rust with C-ABI FFI.","response_excerpt":"[3-Tome Gate: C01 Arch (0.28) + C05 Polyglot Coding (0.39) + C07 AVX2 Perf (0.18) + C08 CWE Security (0.15)]\n• C11/Rust FFI: #[repr(C, align(64))] lock-free ring buffer with saturating bounds checks (0 CWE-125/787).\n• Benchmark & QA: 4.12x AVX2 speedup, 0 ASan/Miri leaks, 94.2% mutation kill score.","recommended_temp":0.15,"recommended_max_tokens":1536},{"bee_index":17,"model_id":"hivemind/moe-image-gen","category":"multimodal_super_moe","architecture":"22.4B 7-Division 104-Bee Image-Gen & Vision-MoE (Janus-Pro + FLUX/SDXL LoRA + Qwen2.5-VL Critic)","active_params_b":2.1,"total_params_b":22.4,"vram_footprint_gb":1.38,"gpu_residency":"100% GPU (<1.5 GB Citizen Micro-VRAM + Big-GPU Diffusion LoRA)","ttft_ms":48.0,"warm_latency_ms":138.4,"tokens_per_sec":114.2,"http_status":200,"hivemind_quality_score":92.9,"frontier_llm_name":"GPT-4o Vision / Midjourney v6 / DALL-E 3","frontier_quality_score":94.2,"frontier_latency_ms":6800.0,"frontier_cost_usd_per_1m":15.0,"daily_usage_sufficiency_pct":95.0,"verdict_badge":"🎨 8.89/10 LAION AESTHETIC • <1.5 GB VRAM","use_case_fr":"Génération d'images (Solarpunk, Ukiyo-e, Anime), schémas d'architecture SVG sans fautes (98,6% OCR), critique visuelle & JWST","use_case_en":"Image generation (Solarpunk, Ukiyo-e, Anime), typo-free architecture diagrams (98.6% OCR), visual critique & JWST","use_case_es":"Generación de imágenes (Solarpunk, Ukiyo-e, Anime), diagramas de arquitectura (98.6% OCR) y visión científica JWST","use_case_de":"Bildgenerierung (Solarpunk, Ukiyo-e, Anime), Architekturdiagramme (98,6% OCR) & wissenschaftliche Vision","use_case_zh":"图像生成 (太阳朋克/浮世绘/动漫)、零拼写错误架构图 (98.6% OCR) 与科学视觉分析","honest_comparison_fr":"Score esthétique LAION de 8,89/10 (contre 7,41 pour un modèle non-routé) et 98,6% de précision typographique sur les schémas techniques grace à la boucle critique Qwen2.5-VL, en utilisant <= 1 410 MiB sur nœud citoyen.","honest_comparison_en":"Achieves an 8.89/10 LAION aesthetic score (vs 7.41 unrouted baseline) and 98.6% diagram typography accuracy via its Qwen2.5-VL critic loop, while using <= 1,410 MiB on citizen nodes.","prompt_tested":"Generate a Solarpunk Ukiyo-e architectural blueprint of a decentralized GPU bee-hive cathedral with verified typography.","response_excerpt":"[FoMoE Gate: DIV-2 Aesthetic Synthesis (0.64) + DIV-4 Diagram & OCR Critic (0.36) | Micro-VRAM: 1,380 MiB]\nSynthesized golden-ratio hexagonal timber arches with Edo Prussian-blue wave motifs; Qwen2.5-VL critic verified 0 diffusion artifacts and 98.6% label legibility (LAION score: 8.94/10).","recommended_temp":0.25,"recommended_max_tokens":768},{"bee_index":18,"model_id":"hivemind/video-moe","category":"multimodal_super_moe","architecture":"28.0B Spatio-Temporal Video-MoE (Wan2.1-T2V + LTX-Video-2B + CogVideoX + 225.4x 3D-DCT)","active_params_b":3.4,"total_params_b":28.0,"vram_footprint_gb":1.34,"gpu_residency":"Hybrid Big-GPU 3D-VAE Keyframes + <1.5 GB Citizen Optical-Flow Verifier","ttft_ms":260.0,"warm_latency_ms":2640.0,"tokens_per_sec":38.4,"http_status":200,"hivemind_quality_score":92.4,"frontier_llm_name":"Sora / Runway Gen-3 / Kling (Proprietary Cloud)","frontier_quality_score":95.0,"frontier_latency_ms":45000.0,"frontier_cost_usd_per_1m":25.0,"daily_usage_sufficiency_pct":91.5,"verdict_badge":"🎬 FVD 41.8 (-38.6%) • 99.12% TEMPORAL CONSISTENCY","use_case_fr":"Vidéo 24/60fps Text-to-Video & Image-to-Video, démos produit IDE animées, storyboards anime & simulations physiques","use_case_en":"24/60fps Text-to-Video & Image-to-Video, animated IDE product demos, anime storyboards & physics simulations","use_case_es":"Vídeo 24/60fps Text-to-Video e Image-to-Video, demos de producto IDE animadas y simulaciones físicas","use_case_de":"24/60fps Text-to-Video & Image-to-Video, animierte IDE-Produktdemos, Storyboards & Physiksimulationen","use_case_zh":"24/60帧文生视频与图生视频、IDE产品演示动画、分镜插帧与物理流体模拟视频","honest_comparison_fr":"Moins destiné aux plans cinéma Hollywood de 60s (-2,6 pts vs Sora), mais pour les clips de 5 à 10s (démos dev, storyboards, visualisations scientifiques), il réduit la FVD de 38,6% (41,8) avec 99,12% de cohérence temporelle.","honest_comparison_en":"Not aimed at 60s Hollywood cinema shots (-2.6 pts vs Sora), but for 5–10s clips (dev product demos, storyboards, scientific visualizations) it cuts FVD by 38.6% (41.8) with 99.12% temporal consistency.","prompt_tested":"Synthesize a 5-second 24fps 720p video sequence of a bioluminescent mechanical bee flying through a rainy cyberpunk alley.","response_excerpt":"[Video-MoE Gate: Wan2.1 Keyframes (0.51) + LTX-Video 24fps Optical Flow (0.31) + Physics Critic (0.18)]\nGenerated 120 frames @ 24fps with 225.4x 3D-DCT latent compression; FVD = 41.8, temporal consistency = 99.12%, verified on <1.5 GB La Ruche edge node (1,340 MiB VRAM).","recommended_temp":0.3,"recommended_max_tokens":1024}]}