Llama 2 70B Chat vs Mistral Large 2
Llama 2 70B Chat (2023) and Mistral Large 2 (2025) are compact production models from AI at Meta and MistralAI. Llama 2 70B Chat ships a 4K-token context window, while Mistral Large 2 ships a 128K-token context window. On Massive Multitask Language Understanding, Mistral Large 2 leads by 15.1 pts. On pricing, Mistral Large 2 costs $0.48/1M input tokens versus $0.5/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
Pick Mistral Large 2 for general evaluation; Llama 2 70B Chat is better when provider fit matters more.
Specs
| Released | 2023-07-18 | 2025-11-25 |
| Context window | 4K | 128K |
| Parameters | 70B | 123B |
| Architecture | decoder only | decoder only |
| License | Open Source | True |
| Knowledge cutoff | - | 2025-07 |
Pricing and availability
| Llama 2 70B Chat | Mistral Large 2 | |
|---|---|---|
| Input price | $0.5/1M tokens | $0.48/1M tokens |
| Output price | $1.5/1M tokens | $2.4/1M tokens |
| Providers |
Capabilities
| Llama 2 70B Chat | Mistral Large 2 | |
|---|---|---|
| Vision | ||
| Multimodal | ||
| Reasoning | ||
| Function calling | ||
| Tool use | ||
| Structured outputs | ||
| Code execution |
Benchmarks
| Benchmark | Llama 2 70B Chat | Mistral Large 2 |
|---|---|---|
| Massive Multitask Language Understanding | 68.9 | 84.0 |
Deep dive
On shared benchmark coverage, Massive Multitask Language Understanding has Llama 2 70B Chat at 68.9 and Mistral Large 2 at 84, with Mistral Large 2 ahead by 15.1 points. The largest visible gap is 15.1 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 vision: Mistral Large 2, multimodal input: Mistral Large 2, function calling: Mistral Large 2, and tool use: Mistral Large 2. Both models share structured outputs, 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 Mistral Large 2 lists $0.48/1M input and $2.4/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Llama 2 70B Chat lower by about $0.26 per million blended tokens. Availability is 14 providers versus 4, so concentration risk also matters.
Choose Llama 2 70B Chat when provider fit and broader provider choice are central to the workload. Choose Mistral Large 2 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 Mistral Large 2?
Mistral Large 2 supports 128K 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 Mistral Large 2?
Mistral Large 2 is cheaper on tracked token pricing. Llama 2 70B Chat costs $0.5/1M input and $1.5/1M output tokens. Mistral Large 2 costs $0.48/1M input and $2.4/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Llama 2 70B Chat or Mistral Large 2 open source?
Llama 2 70B Chat is listed under Open Source. Mistral Large 2 is listed under True. 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 vision, Llama 2 70B Chat or Mistral Large 2?
Mistral Large 2 has the clearer documented vision signal in this comparison. If vision is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Which is better for multimodal input, Llama 2 70B Chat or Mistral Large 2?
Mistral Large 2 has the clearer documented multimodal input signal in this comparison. If multimodal input 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 Mistral Large 2?
Llama 2 70B Chat is available on Databricks Foundation Model Serving, Microsoft Foundry, GCP Vertex AI, Alibaba Cloud PAI-EAS, and AWS Bedrock. Mistral Large 2 is available on OpenRouter, IBM watsonx, AWS Bedrock, and Mistral AI Studio. 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.