Llama 4 Behemoth vs Aion-Mini
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (4)
Compare Llama 4 Behemoth by Meta against Aion-Mini by AionLabs across real-world coding, reasoning, token economics, and latency.
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Llama 4 Behemoth
开源权重模型Meta 推出的 Llama 4 Behemoth 人工智能模型，具备 10M 上下文窗口，输入价格为 $0/百万 Token，输出价格为 $0/百万 Token，专为高质量生产环境、推理与自动化工作流打造。
$0.00 / 1M
$0.00 / 1M
10M tokens
75%
Aion-Mini
深度推理模型AionLabs 推出的 Aion-Mini 人工智能模型，具备 131K 上下文窗口，输入价格为 $0.08/百万 Token，输出价格为 $0.32/百万 Token，专为高质量生产环境、推理与自动化工作流打造。
$0.08 / 1M
$0.32 / 1M
131.1K tokens
N/A
核心差异一览
- Llama 4 Behemoth is 1.0x cheaper for API usage (input + output tokens combined).
- Llama 4 Behemoth has a larger context window (10M vs 131K tokens).
- Aion-Mini is faster at 150 tok/s vs 45 tok/s.
| Feature | Llama 4 Behemoth | Aion-Mini |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 93 | 74 |
Provider | Meta | AionLabs |
Input Price Cost per million input tokens | $0.00 / 1M | $0.08 / 1M |
Output Price Cost per million output tokens | $0.00 / 1M | $0.32 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $0.00 / 1M | $0.05 / 1M |
Context Window Maximum input + output tokens | 10M tokens~15,000 A4 pages of text | 131.1K tokens~197 A4 pages of text |
Max Output Tokens Per single request | 64K | 8K |
Throughput Speed Tokens generated per second | 45 tok/s | 150 tok/s |
SWE-bench Verified Real-world software engineering | 75% | N/A |
GPQA Diamond Graduate-level reasoning | 82% | N/A |
Cached Input Price Prompt caching discount per 1M tokens | $0.00 / 1M | $0.01 / 1M |
各项指标谁更胜一筹？
At-a-glance decision frameworkEvaluations ongoing
权威基准测试得分对比
Official evaluation metrics verified by independent third-party research labs.
Industry benchmark evaluating real-world GitHub issue resolution and multi-file debugging.
Challenging questions created by domain experts to test complex PhD-level reasoning.
Hardened reasoning and academic knowledge benchmark with reduced lucky-guess probability.
Crowdsourced human preference evaluation based on blind, head-to-head model battles.
Accuracy when reasoning over very large inputs that fill the model context window.
Tokens emitted per second during active generation streaming.
延迟与响应速度
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
实时 Token 成本模拟器
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
Llama 4 Behemoth · Strengths & Key Advantages
- 由 Meta 研发的高精度 Colossal sparse MoE architecture (288B active / 2T total, 16-of-2 MoE) 架构，支持 10M 上下文窗口
- 极具竞争力的 API 定价（输入 $0/1M，输出 $0/1M），支持高速推理与工具调用
- 在代码生成、逻辑推理与多语言处理基准测试中表现出色
Considerations & Trade-offs
- 超长上下文请求需要规划 Token 成本与并发配额
- 针对特定垂直领域任务建议结合系统提示词与检索增强（RAG）以获得最佳效果
Aion-Mini · Strengths & Key Advantages
- 由 AionLabs 研发的高精度 Compact Scientific Routing Transformer 架构，支持 131K 上下文窗口
- 极具竞争力的 API 定价（输入 $0.08/1M，输出 $0.32/1M），支持高速推理与工具调用
- 在代码生成、逻辑推理与多语言处理基准测试中表现出色
Considerations & Trade-offs
- 超长上下文请求需要规划 Token 成本与并发配额
- 针对特定垂直领域任务建议结合系统提示词与检索增强（RAG）以获得最佳效果
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | Llama 4 Behemoth | Aion-Mini |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.00 | $0.03 |
Output Tokens / Task Tokens generated per task | 35K | 10K |
Reasoning Tokens / Task Thinking tokens burned per task | 15K | 1K |
技术规格参数
Architecture, release timeline, capabilities, and modalities.
| Feature | Llama 4 Behemoth | Aion-Mini |
|---|---|---|
| Official API Model ID (SDK) | meta-llama/Llama-4-Behemoth | aion-mini |
| API Protocol | OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI | AionLabs REST API (OpenAI-Compatible) |
| Release Date | 2026-05 | 2026-07 |
| Knowledge Cutoff | February 2026 | May 2026 |
| Architecture | Colossal sparse MoE architecture (288B active / 2T total, 16-of-2 MoE) | Compact Scientific Routing Transformer |
| Parameters | 2T total / 288B active (16-of-2 MoE) | Confidential |
| Enterprise Rate Limits (RPM / TPM) | Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud | 5,000 – 15,000 RPM (Production Tier) · 800,000 – 2,000,000 TPM |
| Long-Context Tier (>128K/200K) | Free across full context window (only KV-cache VRAM scales) | Flat rate ($0.08/1M in) across full 131K window |
| Prompt Cache Policy & TTL | Automatic prefix KV-caching in vLLM / SGLang (0 cost) | Cached input at $0.008/1M tokens |
| Computer Use / GUI Agent | Supported (Screen coordinate grounding, browser & desktop GUI action loops) | API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop) |
| MCP & Parallel Tool Calling | Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema | Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema |
| Web Search Grounding & Sandbox | Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools | Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools |
| Official Fine-Tuning Support | Full Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory) | API Prompt Engineering & RAG Distillation |
| Multimodal Token Billing | Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) | Text BPE (~4 chars/token) |
| Quantization & Min GPU VRAM | BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 1240 GB VRAM (4-bit Quantized) · 4300 GB VRAM (Native BF16) | Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API) |
| Safety & Frontier Classification | Open-Weights System Card + Customizable Guardrail Layer (Llama Guard / ShieldGemma) | AionLabs Production Safety & Alignment Verified |
| Enterprise Compliance (ZDR/HIPAA/SOC2) | 100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control | SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier |
| Input Modalities | text, vision | text |
| Output Modalities | text | text |
Llama 4 Behemoth vs Aion-Mini: 常见问题解答 (FAQ)
Which is more intelligent, Llama 4 Behemoth or Aion-Mini?
Llama 4 Behemoth is more intelligent. It scores 93 compared with 74 on the composite Intelligence Index.
Which model is faster?
Aion-Mini is faster, generating 150 tokens per second compared with 45 tokens per second.
Which model is cheaper to run?
Llama 4 Behemoth is cheaper at $0.00 per 1M tokens blended, compared with $0.05 (7:2:1 cache:input:output ratio).
Which model has lower latency?
Aion-Mini has lower latency, with a time to first token of 0.28s compared with 1.20s.
Which model has a larger context window?
Llama 4 Behemoth has a larger context window, supporting 10M tokens compared with 131.1K tokens.
综合结论
Choose Llama 4 Behemoth for 企业级 ai 自动化、代码研发、智能体（agent）工作流以及 meta 生态深度集成, or choose Aion-Mini for 企业级 ai 自动化、代码研发、智能体（agent）工作流以及 aionlabs 生态深度集成.
常见问题 (FAQ)
Which is cheaper: Llama 4 Behemoth or Aion-Mini?+
Llama 4 Behemoth costs $0/1M input and $0/1M output tokens, while Aion-Mini costs $0.08/1M input and $0.32/1M output tokens.
Which model has a larger context window: Llama 4 Behemoth or Aion-Mini?+
Llama 4 Behemoth supports 10M tokens whereas Aion-Mini supports 131K tokens.
Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.
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Benchmark scores, token prices, and rate limits evolve rapidly as AI labs release model updates. Always verify current specifications and pricing on the official provider documentation.
数据来源: Meta & AionLabs Official Documentation