Llama 3.1 70B Instruct vs Mistral Nemotron
Llama 3.1 70B Instruct (2024) and Mistral Nemotron (2025) are compact production models from AI at Meta and MistralAI. Llama 3.1 70B Instruct ships a 128k-token context window, while Mistral Nemotron ships a not-yet-sourced context window. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads. It focuses on practical selection signals rather than broad model-family marketing.
Mistral Nemotron is safer overall; choose Llama 3.1 70B Instruct when provider fit matters.
Decision scorecard
Local evidence first| Signal | Llama 3.1 70B Instruct | Mistral Nemotron |
|---|---|---|
| Best for | provider-routed production | general production evaluation |
| Decision fit | Coding, RAG, and Long context | General |
| Context window | 128k | — |
| Cheapest output | $0.40/1M tokens | - |
| Provider routes | 13 tracked | 1 tracked |
| Shared benchmarks | 0 shared | 0 shared |
Decision tradeoffs
- Llama 3.1 70B Instruct has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Llama 3.1 70B Instruct has broader tracked provider coverage for fallback and route flexibility.
- Llama 3.1 70B Instruct uniquely exposes Structured outputs in local model data.
- Local decision data tags Llama 3.1 70B Instruct for Coding, RAG, and Long context.
- Use Mistral Nemotron when your own prompt tests beat the comparison signals; the local data does not show a decisive standalone advantage yet.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
Llama 3.1 70B Instruct
$420
Cheapest tracked route/tier: Hyperbolic AI Inference
Mistral Nemotron
Unavailable
No complete token price in local provider data
Cost delta unavailable until both models have sourced input and output token prices.
Switch friction
- Provider overlap exists on NVIDIA NIM; start route-level A/B tests there.
- Check replacement coverage for Structured outputs before moving production traffic.
- Provider overlap exists on NVIDIA NIM; start route-level A/B tests there.
- Llama 3.1 70B Instruct adds Structured outputs in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2024-07-23 | 2025-12-01 |
| Context window | 128k | — |
| Parameters | 70B | 70B |
| Architecture | Decoder Only | Decoder Only |
| License | Llama 3 Community | Proprietary |
| Openness | Open weights | Proprietary |
| Weights | Available | Not released |
| Code | Unknown | Unknown |
| Commercial use | Commercial use: conditional | - |
| Knowledge cutoff | 2023-12 | - |
Pricing and availability
| Pricing attribute | Llama 3.1 70B Instruct | Mistral Nemotron |
|---|---|---|
| Input price | $0.40/1M tokens | - |
| Output price | $0.40/1M tokens | - |
| Providers |
Capabilities
| Capability | Llama 3.1 70B Instruct | Mistral Nemotron |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | No | No |
| JSON / Tool use | No | No |
| Structured outputs | Yes | No |
| Code execution | No | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
No shared benchmark scores are currently available for this pair.
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Last reviewed: 2026-07-11. Data sourced from public model cards and provider documentation.