Llama 3 70B Instruct vs Mistral Large 2 (2407)
Llama 3 70B Instruct (2024) and Mistral Large 2 (2407) (2024) are compact production models from AI at Meta and MistralAI. Llama 3 70B Instruct ships a 8K-token context window, while Mistral Large 2 (2407) ships a 128K-token context window. On MMLU PRO, Mistral Large 2 (2407) leads by 8.5 pts. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.
Mistral Large 2 (2407) fits 16x more tokens; pick it for long-context work and Llama 3 70B Instruct for tighter calls.
Decision scorecard
Local evidence first| Signal | Llama 3 70B Instruct | Mistral Large 2 (2407) |
|---|---|---|
| Best for | provider-routed production | tool-calling agents and provider-routed production |
| Decision fit | Coding, Classification, and JSON / Tool use | Coding, RAG, and Agents |
| Context window | 8K | 128K |
| Cheapest output | $0.40/1M tokens | $1.50/1M tokens |
| Provider routes | 18 tracked | 7 tracked |
| Shared benchmarks | 3 shared | MMLU PRO leader |
Decision tradeoffs
- Llama 3 70B Instruct has the lower cheapest tracked output price at $0.40/1M tokens.
- Llama 3 70B Instruct has broader tracked provider coverage for fallback and route flexibility.
- Local decision data tags Llama 3 70B Instruct for Coding, Classification, and JSON / Tool use.
- Mistral Large 2 (2407) holds a shared-benchmark lead on MMLU PRO, ahead by 8.5 points.
- Mistral Large 2 (2407) has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Mistral Large 2 (2407) uniquely exposes JSON / Tool use in local model data.
- Local decision data tags Mistral Large 2 (2407) for Coding, RAG, and Agents.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
Llama 3 70B Instruct
$420
Cheapest tracked route/tier: Hyperbolic AI Inference
Mistral Large 2 (2407)
$775
Cheapest tracked route/tier: Chutes AI
Estimated monthly gap: $355. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on Microsoft Foundry, IBM watsonx, and OpenRouter; start route-level A/B tests there.
- Mistral Large 2 (2407) is $1.10/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Mistral Large 2 (2407) adds JSON / Tool use in local capability data.
- Provider overlap exists on AWS Bedrock, Microsoft Foundry, and IBM watsonx; start route-level A/B tests there.
- Llama 3 70B Instruct is $1.10/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for JSON / Tool use before moving production traffic.
Specs
| Specification | ||
|---|---|---|
| Released | 2024-04-18 | 2024-07-24 |
| Context window | 8K | 128K |
| Parameters | 70B | 123B |
| Architecture | Decoder Only | Decoder Only |
| License | Llama 3 Community | Mistral License |
| Openness | Open weights | Open weights |
| Weights | Available | Available |
| Code | Unknown | Unknown |
| Commercial use | Restricted | Not permitted |
| Knowledge cutoff | 2023-12 | 2024-03 |
Pricing and availability
| Pricing attribute | Llama 3 70B Instruct | Mistral Large 2 (2407) |
|---|---|---|
| Input price | $0.40/1M tokens | $0.50/1M tokens |
| Output price | $0.40/1M tokens | $1.50/1M tokens |
| Providers |
Capabilities
| Capability | Llama 3 70B Instruct | Mistral Large 2 (2407) |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | No | No |
| JSON / Tool use | No | Yes |
| Structured outputs | Yes | Yes |
| Code execution | No | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
| Benchmark | Llama 3 70B Instruct | Mistral Large 2 (2407) |
|---|---|---|
| MMLU PRO | 57.4 | 65.9 |
| HumanEval | 72.6 | 92.0 |
| Massive Multitask Language Understanding | 82.0 | 84.0 |
Deep dive
On shared benchmark coverage, MMLU PRO has Llama 3 70B Instruct at 57.4 and Mistral Large 2 (2407) at 65.9, with Mistral Large 2 (2407) ahead by 8.5 points; HumanEval has Llama 3 70B Instruct at 72.6 and Mistral Large 2 (2407) at 92, with Mistral Large 2 (2407) ahead by 19.4 points; Massive Multitask Language Understanding has Llama 3 70B Instruct at 82 and Mistral Large 2 (2407) at 84, with Mistral Large 2 (2407) ahead by 2 points. The largest visible gap is 19.4 points on HumanEval, 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 JSON / Tool use: Mistral Large 2 (2407). 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 3 70B Instruct lists $0.40/1M input and $0.40/1M output tokens on the cheapest tracked provider, while Mistral Large 2 (2407) lists $0.50/1M input and $1.50/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Llama 3 70B Instruct lower by about $0.40 per million blended tokens. Availability is 18 providers versus 7, so concentration risk also matters.
Choose Llama 3 70B Instruct when provider fit, lower input-token cost, and broader provider choice are central to the workload. Choose Mistral Large 2 (2407) 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.
FAQ
Which has a larger context window, Llama 3 70B Instruct or Mistral Large 2 (2407)?
Mistral Large 2 (2407) supports 128K tokens, while Llama 3 70B Instruct supports 8K 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 3 70B Instruct or Mistral Large 2 (2407)?
Llama 3 70B Instruct is cheaper on tracked token pricing. Llama 3 70B Instruct costs $0.40/1M input and $0.40/1M output tokens. Mistral Large 2 (2407) costs $0.50/1M input and $1.50/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Llama 3 70B Instruct or Mistral Large 2 (2407) open source?
Llama 3 70B Instruct is listed under Llama 3 Community. Mistral Large 2 (2407) is listed under Mistral License. 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 JSON / Tool use, Llama 3 70B Instruct or Mistral Large 2 (2407)?
Mistral Large 2 (2407) has the clearer documented JSON / Tool use signal in this comparison. If JSON / Tool use 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 3 70B Instruct or Mistral Large 2 (2407)?
Both Llama 3 70B Instruct and Mistral Large 2 (2407) expose structured outputs. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface.
Where can I run Llama 3 70B Instruct and Mistral Large 2 (2407)?
Llama 3 70B Instruct is available on GCP Vertex AI, AWS Bedrock, Microsoft Foundry, NVIDIA NIM, and DeepInfra. Mistral Large 2 (2407) is available on Microsoft Foundry, IBM watsonx, OpenRouter, AWS Bedrock, and Chutes AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
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Last reviewed: 2026-10-17. Data sourced from public model cards and provider documentation.