Llama 2 70B Chat vs Mixtral 8x22B v0.1
Llama 2 70B Chat (2023) and Mixtral 8x22B v0.1 (2024) are compact production models from AI at Meta and MistralAI. Llama 2 70B Chat ships a 4K-token context window, while Mixtral 8x22B v0.1 ships a 64K-token context window. On Massive Multitask Language Understanding, Mixtral 8x22B v0.1 leads by 15.6 pts. On pricing, Mixtral 8x22B v0.1 costs $0.3/1M input tokens versus $0.5/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
Mixtral 8x22B v0.1 is ~67% cheaper at $0.3/1M; pay for Llama 2 70B Chat only for provider fit.
Specs
| Released | 2023-07-18 | 2024-04-17 |
| 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 v0.1 | |
|---|---|---|
| Input price | $0.5/1M tokens | $0.3/1M tokens |
| Output price | $1.5/1M tokens | $0.9/1M tokens |
| Providers |
Capabilities
| Llama 2 70B Chat | Mixtral 8x22B v0.1 | |
|---|---|---|
| Vision | ||
| Multimodal | ||
| Reasoning | ||
| Function calling | ||
| Tool use | ||
| Structured outputs | ||
| Code execution |
Benchmarks
| Benchmark | Llama 2 70B Chat | Mixtral 8x22B v0.1 |
|---|---|---|
| Massive Multitask Language Understanding | 68.9 | 84.5 |
Deep dive
On shared benchmark coverage, Massive Multitask Language Understanding has Llama 2 70B Chat at 68.9 and Mixtral 8x22B v0.1 at 84.5, with Mixtral 8x22B v0.1 ahead by 15.6 points. The largest visible gap is 15.6 points on Massive Multitask Language Understanding, which matters most when that benchmark mirrors your workload. Treat isolated benchmark wins as directional, because provider routing, prompt style, and tool access can move real application results.
The capability footprint differs most on 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 v0.1 lists $0.3/1M input and $0.9/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Mixtral 8x22B v0.1 lower by about $0.32 per million blended tokens. Availability is 14 providers versus 8, so concentration risk also matters.
Choose Llama 2 70B Chat when provider fit and broader provider choice are central to the workload. Choose Mixtral 8x22B v0.1 when long-context analysis, larger context windows, and lower input-token cost are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship.
FAQ
Which has a larger context window, Llama 2 70B Chat or Mixtral 8x22B v0.1?
Mixtral 8x22B v0.1 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 v0.1?
Mixtral 8x22B v0.1 is cheaper on tracked token pricing. Llama 2 70B Chat costs $0.5/1M input and $1.5/1M output tokens. Mixtral 8x22B v0.1 costs $0.3/1M input and $0.9/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Llama 2 70B Chat or Mixtral 8x22B v0.1 open source?
Llama 2 70B Chat is listed under Open Source. Mixtral 8x22B v0.1 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 structured outputs, Llama 2 70B Chat or Mixtral 8x22B v0.1?
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 v0.1?
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 v0.1 is available on NVIDIA NIM, OctoAI API, Fireworks AI, DeepInfra, and Baseten API. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
When should I pick Llama 2 70B Chat over Mixtral 8x22B v0.1?
Mixtral 8x22B v0.1 is ~67% cheaper at $0.3/1M; pay for Llama 2 70B Chat only for provider fit. If your workload also depends on provider fit, start with Llama 2 70B Chat; if it depends on long-context analysis, run the same evaluation with Mixtral 8x22B v0.1.
Continue comparing
Last reviewed: 2026-04-24. Data sourced from public model cards and provider documentation.