Llama 3.1 Nemotron Nano 4B v1.1 vs Mistral Large 3 675B Instruct
Llama 3.1 Nemotron Nano 4B v1.1 (2025) and Mistral Large 3 675B Instruct (2025) are compact production models from NVIDIA AI and MistralAI. Llama 3.1 Nemotron Nano 4B v1.1 ships a 4k-token context window, while Mistral Large 3 675B Instruct ships a 128k-token context window. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.
Mistral Large 3 675B Instruct fits 32x more tokens; pick it for long-context work and Llama 3.1 Nemotron Nano 4B v1.1 for tighter calls.
Decision scorecard
Local evidence first| Signal | Llama 3.1 Nemotron Nano 4B v1.1 | Mistral Large 3 675B Instruct |
|---|---|---|
| Best for | general production evaluation | multimodal apps and provider-routed production |
| Decision fit | General | Coding, RAG, and Agents |
| Context window | 4k | 128k |
| Cheapest output | - | $1.50/1M tokens |
| Provider routes | 1 tracked | 6 tracked |
| Shared benchmarks | 0 shared | 0 shared |
Decision tradeoffs
- Use Llama 3.1 Nemotron Nano 4B v1.1 when your own prompt tests beat the comparison signals; the local data does not show a decisive standalone advantage yet.
- Mistral Large 3 675B Instruct has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Mistral Large 3 675B Instruct has broader tracked provider coverage for fallback and procurement flexibility.
- Mistral Large 3 675B Instruct uniquely exposes Vision, Multimodal, and Structured outputs in local model data.
- Local decision data tags Mistral Large 3 675B Instruct 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 3.1 Nemotron Nano 4B v1.1
Unavailable
No complete token price in local provider data
Mistral Large 3 675B Instruct
$775
Cheapest tracked route/tier: OpenRouter
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.
- Mistral Large 3 675B Instruct adds Vision, Multimodal, and Structured outputs in local capability data.
- Provider overlap exists on NVIDIA NIM; start route-level A/B tests there.
- Check replacement coverage for Vision, Multimodal, and Structured outputs before moving production traffic.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-04-01 | 2025-12-01 |
| Context window | 4k | 128k |
| Parameters | 4B | 675B |
| Architecture | Decoder Only | Decoder Only |
| License | Llama 3 Community | Apache 2.0OSI-approved |
| Openness | Open weights | Open source |
| Weights | Unknown | Unknown |
| Code | Unknown | Unknown |
| Commercial use | Commercial use: conditional | Commercial use: permitted |
| Knowledge cutoff | - | 2024-11 |
Pricing and availability
| Pricing attribute | Llama 3.1 Nemotron Nano 4B v1.1 | Mistral Large 3 675B Instruct |
|---|---|---|
| Input price | - | $0.50/1M tokens |
| Output price | - | $1.50/1M tokens |
| Providers |
Capabilities
| Capability | Llama 3.1 Nemotron Nano 4B v1.1 | Mistral Large 3 675B Instruct |
|---|---|---|
| Vision | No | Yes |
| Multimodal | No | Yes |
| Reasoning | No | No |
| Function calling | No | No |
| Tool use | No | No |
| Structured outputs | No | Yes |
| 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.
Deep dive
The capability footprint differs most on vision: Mistral Large 3 675B Instruct, multimodal input: Mistral Large 3 675B Instruct, and structured outputs: Mistral Large 3 675B 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.
Pricing coverage is uneven: Llama 3.1 Nemotron Nano 4B v1.1 has no token price sourced yet and Mistral Large 3 675B Instruct has $0.50/1M input tokens. Provider availability is 1 tracked routes versus 6. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.
Choose Llama 3.1 Nemotron Nano 4B v1.1 when provider fit are central to the workload. Choose Mistral Large 3 675B Instruct when long-context analysis, larger context windows, and broader provider choice 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.
FAQ
Which has a larger context window, Llama 3.1 Nemotron Nano 4B v1.1 or Mistral Large 3 675B Instruct?
Mistral Large 3 675B Instruct supports 128k tokens, while Llama 3.1 Nemotron Nano 4B v1.1 supports 4k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Is Llama 3.1 Nemotron Nano 4B v1.1 or Mistral Large 3 675B Instruct open source?
Llama 3.1 Nemotron Nano 4B v1.1 is listed under Llama 3 Community. Mistral Large 3 675B Instruct 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 vision, Llama 3.1 Nemotron Nano 4B v1.1 or Mistral Large 3 675B Instruct?
Mistral Large 3 675B Instruct 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 3.1 Nemotron Nano 4B v1.1 or Mistral Large 3 675B Instruct?
Mistral Large 3 675B Instruct 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.
Which is better for structured outputs, Llama 3.1 Nemotron Nano 4B v1.1 or Mistral Large 3 675B Instruct?
Mistral Large 3 675B 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 3.1 Nemotron Nano 4B v1.1 and Mistral Large 3 675B Instruct?
Llama 3.1 Nemotron Nano 4B v1.1 is available on NVIDIA NIM. Mistral Large 3 675B Instruct is available on OpenRouter, AWS Bedrock, NVIDIA NIM, Mistral AI Studio, and Microsoft Foundry. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
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Last reviewed: 2026-06-29. Data sourced from public model cards and provider documentation.