Llama 3 70B Instruct vs Mistral 7B v0.1
Llama 3 70B Instruct (2024) and Mistral 7B v0.1 (2023) are compact production models from AI at Meta and MistralAI. Llama 3 70B Instruct ships a 8K-token context window, while Mistral 7B v0.1 ships a 8K-token context window. On pricing, Mistral 7B v0.1 costs $0.05/1M input tokens versus $0.4/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
Mistral 7B v0.1 is ~700% cheaper at $0.05/1M; pay for Llama 3 70B Instruct only for provider fit.
Decision scorecard
Local evidence first| Signal | Llama 3 70B Instruct | Mistral 7B v0.1 |
|---|---|---|
| Decision fit | Coding, Classification, and JSON / Tool use | General |
| Context window | 8K | 8K |
| Cheapest output | $0.4/1M tokens | $0.15/1M tokens |
| Provider routes | 17 tracked | 16 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Llama 3 70B Instruct has broader tracked provider coverage for fallback and procurement flexibility.
- Llama 3 70B Instruct uniquely exposes Structured outputs in local model data.
- Local decision data tags Llama 3 70B Instruct for Coding, Classification, and JSON / Tool use.
- Mistral 7B v0.1 has the lower cheapest tracked output price at $0.15/1M tokens.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output prices on this page.
Llama 3 70B Instruct
$420
Cheapest tracked route: Hyperbolic AI Inference
Mistral 7B v0.1
$77.50
Cheapest tracked route: DeepInfra
Estimated monthly gap: $343. Batch, cache, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on GCP Vertex AI, OctoAI API (Deprecated), and DeepInfra; start route-level A/B tests there.
- Mistral 7B v0.1 is $0.25/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Structured outputs before moving production traffic.
- Provider overlap exists on GCP Vertex AI, AWS Bedrock, and Microsoft Foundry; start route-level A/B tests there.
- Llama 3 70B Instruct is $0.25/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Llama 3 70B Instruct adds Structured outputs in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2024-04-18 | 2023-09-27 |
| Context window | 8K | 8K |
| Parameters | 70B | 7B |
| Architecture | decoder only | decoder only |
| License | Open Source | Apache 2.0 |
| Knowledge cutoff | 2023-12 | 2023-12 |
Pricing and availability
| Pricing attribute | Llama 3 70B Instruct | Mistral 7B v0.1 |
|---|---|---|
| Input price | $0.4/1M tokens | $0.05/1M tokens |
| Output price | $0.4/1M tokens | $0.15/1M tokens |
| Providers |
Capabilities
| Capability | Llama 3 70B Instruct | Mistral 7B v0.1 |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | No | No |
| Function calling | No | No |
| Tool use | No | No |
| Structured outputs | Yes | No |
| Code execution | No | No |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on structured outputs: Llama 3 70B Instruct. 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 3 70B Instruct lists $0.4/1M input and $0.4/1M output tokens, while Mistral 7B v0.1 lists $0.05/1M input and $0.15/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Mistral 7B v0.1 lower by about $0.32 per million blended tokens. Availability is 17 providers versus 16, so concentration risk also matters.
Choose Llama 3 70B Instruct when provider fit and broader provider choice are central to the workload. Choose Mistral 7B v0.1 when provider fit 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. This keeps the decision grounded in measurable tradeoffs instead of brand-level assumptions. It also helps separate model capability from provider packaging, which can change cost and latency.
FAQ
Which has a larger context window, Llama 3 70B Instruct or Mistral 7B v0.1?
Llama 3 70B Instruct supports 8K tokens, while Mistral 7B v0.1 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 7B v0.1?
Mistral 7B v0.1 is cheaper on tracked token pricing. Llama 3 70B Instruct costs $0.4/1M input and $0.4/1M output tokens. Mistral 7B v0.1 costs $0.05/1M input and $0.15/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Llama 3 70B Instruct or Mistral 7B v0.1 open source?
Llama 3 70B Instruct is listed under Open Source. Mistral 7B 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 3 70B Instruct or Mistral 7B v0.1?
Llama 3 70B Instruct 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 3 70B Instruct and Mistral 7B v0.1?
Llama 3 70B Instruct is available on GCP Vertex AI, AWS Bedrock, Microsoft Foundry, NVIDIA NIM, and DeepInfra. Mistral 7B v0.1 is available on GCP Vertex AI, OctoAI API (Deprecated), DeepInfra, Mistral AI Studio, and Baseten API. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
When should I pick Llama 3 70B Instruct over Mistral 7B v0.1?
Mistral 7B v0.1 is ~700% cheaper at $0.05/1M; pay for Llama 3 70B Instruct only for provider fit. If your workload also depends on provider fit, start with Llama 3 70B Instruct; if it depends on provider fit, run the same evaluation with Mistral 7B v0.1.
Continue comparing
Last reviewed: 2026-05-16. Data sourced from public model cards and provider documentation.