Llama 2 70B Chat vs Mixtral 8x22B Instruct v0.3
Llama 2 70B Chat (2023) and Mixtral 8x22B Instruct v0.3 (2024) are compact production models from AI at Meta and MistralAI. Llama 2 70B Chat ships a 4K-token context window, while Mixtral 8x22B Instruct v0.3 ships a 64K-token context window. On pricing, Llama 2 70B Chat costs $0.5/1M input tokens versus $2/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
Llama 2 70B Chat is ~300% cheaper at $0.5/1M; pay for Mixtral 8x22B Instruct v0.3 only for long-context analysis.
Specs
| Released | 2023-07-18 | 2024-07-01 |
| Context window | 4K | 64K |
| Parameters | 70B | 8x22B |
| Architecture | decoder only | mixture of experts |
| License | Open Source | Apache 2.0 |
| Knowledge cutoff | - | - |
Pricing and availability
| Llama 2 70B Chat | Mixtral 8x22B Instruct v0.3 | |
|---|---|---|
| Input price | $0.5/1M tokens | $2/1M tokens |
| Output price | $1.5/1M tokens | $2/1M tokens |
| Providers |
Capabilities
| Llama 2 70B Chat | Mixtral 8x22B Instruct v0.3 | |
|---|---|---|
| Vision | ||
| Multimodal | ||
| Reasoning | ||
| Function calling | ||
| Tool use | ||
| Structured outputs | ||
| Code execution |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on function calling: Mixtral 8x22B Instruct v0.3 and structured outputs: Llama 2 70B Chat. Both models share the core language-model surface, so the practical split is not just feature count. Use those differences to decide whether the page is about raw model quality, agentic coding support, multimodal ingestion, or predictable structured API behavior.
For cost, Llama 2 70B Chat lists $0.5/1M input and $1.5/1M output tokens, while Mixtral 8x22B Instruct v0.3 lists $2/1M input and $2/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Llama 2 70B Chat lower by about $1.2 per million blended tokens. Availability is 14 providers versus 1, so concentration risk also matters.
Choose Llama 2 70B Chat when provider fit, lower input-token cost, and broader provider choice are central to the workload. Choose Mixtral 8x22B Instruct v0.3 when long-context analysis and larger context windows are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship. This keeps the decision grounded in measurable tradeoffs instead of brand-level assumptions.
FAQ
Which has a larger context window, Llama 2 70B Chat or Mixtral 8x22B Instruct v0.3?
Mixtral 8x22B Instruct v0.3 supports 64K tokens, while Llama 2 70B Chat supports 4K tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Which is cheaper, Llama 2 70B Chat or Mixtral 8x22B Instruct v0.3?
Llama 2 70B Chat is cheaper on tracked token pricing. Llama 2 70B Chat costs $0.5/1M input and $1.5/1M output tokens. Mixtral 8x22B Instruct v0.3 costs $2/1M input and $2/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Llama 2 70B Chat or Mixtral 8x22B Instruct v0.3 open source?
Llama 2 70B Chat is listed under Open Source. Mixtral 8x22B Instruct v0.3 is listed under Apache 2.0. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.
Which is better for function calling, Llama 2 70B Chat or Mixtral 8x22B Instruct v0.3?
Mixtral 8x22B Instruct v0.3 has the clearer documented function calling signal in this comparison. If function calling is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Which is better for structured outputs, Llama 2 70B Chat or Mixtral 8x22B Instruct v0.3?
Llama 2 70B Chat has the clearer documented structured outputs signal in this comparison. If structured outputs is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run Llama 2 70B Chat and Mixtral 8x22B Instruct v0.3?
Llama 2 70B Chat is available on Databricks Foundation Model Serving, Microsoft Foundry, GCP Vertex AI, Alibaba Cloud PAI-EAS, and AWS Bedrock. Mixtral 8x22B Instruct v0.3 is available on Replicate API. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
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Last reviewed: 2026-04-24. Data sourced from public model cards and provider documentation.