Mistral Large 3 675B Instruct vs Nemotron-Nano-9B-v2
Mistral Large 3 675B Instruct (2025) and Nemotron-Nano-9B-v2 (2025) are compact production models from MistralAI and NVIDIA AI. Mistral Large 3 675B Instruct ships a 128K-token context window, while Nemotron-Nano-9B-v2 ships a not-yet-sourced context window. On pricing, Nemotron-Nano-9B-v2 costs $0.04/1M input tokens versus $0.5/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit. It focuses on practical selection signals rather than broad model-family marketing.
Nemotron-Nano-9B-v2 is ~1150% cheaper at $0.04/1M; pay for Mistral Large 3 675B Instruct only for provider fit.
Decision scorecard
Local evidence first| Signal | Mistral Large 3 675B Instruct | Nemotron-Nano-9B-v2 |
|---|---|---|
| Decision fit | Coding, RAG, and Agents | Classification and JSON / Tool use |
| Context window | 128K | — |
| Cheapest output | $1.5/1M tokens | $0.16/1M tokens |
| Provider routes | 4 tracked | 2 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- 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.
- Local decision data tags Mistral Large 3 675B Instruct for Coding, RAG, and Agents.
- Nemotron-Nano-9B-v2 has the lower cheapest tracked output price at $0.16/1M tokens.
- Local decision data tags Nemotron-Nano-9B-v2 for Classification and JSON / Tool use.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output prices on this page.
Mistral Large 3 675B Instruct
$775
Cheapest tracked route: AWS Bedrock
Nemotron-Nano-9B-v2
$72.00
Cheapest tracked route: OpenRouter
Estimated monthly gap: $703. Batch, cache, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on NVIDIA NIM; start route-level A/B tests there.
- Nemotron-Nano-9B-v2 is $1.34/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Provider overlap exists on NVIDIA NIM; start route-level A/B tests there.
- Mistral Large 3 675B Instruct is $1.34/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-12-01 | 2025-08-18 |
| Context window | 128K | — |
| Parameters | 675B | 9B |
| Architecture | decoder only | decoder only |
| License | 1 | Unknown |
| Knowledge cutoff | 2024-11 | 2025-03 |
Pricing and availability
| Pricing attribute | Mistral Large 3 675B Instruct | Nemotron-Nano-9B-v2 |
|---|---|---|
| Input price | $0.5/1M tokens | $0.04/1M tokens |
| Output price | $1.5/1M tokens | $0.16/1M tokens |
| Providers |
Capabilities
| Capability | Mistral Large 3 675B Instruct | Nemotron-Nano-9B-v2 |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | No | No |
| Function calling | No | No |
| Tool use | No | No |
| Structured outputs | Yes | Yes |
| Code execution | No | No |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint is close: both models cover structured outputs. That makes context budget, benchmark fit, and provider maturity more important than a simple checklist. If your application depends on one integration detail, verify it against the provider route you plan to use, not just the base model listing.
For cost, Mistral Large 3 675B Instruct lists $0.5/1M input and $1.5/1M output tokens, while Nemotron-Nano-9B-v2 lists $0.04/1M input and $0.16/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Nemotron-Nano-9B-v2 lower by about $0.72 per million blended tokens. Availability is 4 providers versus 2, so concentration risk also matters.
Choose Mistral Large 3 675B Instruct when provider fit and broader provider choice are central to the workload. Choose Nemotron-Nano-9B-v2 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. For teams standardizing a stack, that distinction is often the difference between a benchmark win and a reliable deployment.
FAQ
Which is cheaper, Mistral Large 3 675B Instruct or Nemotron-Nano-9B-v2?
Nemotron-Nano-9B-v2 is cheaper on tracked token pricing. Mistral Large 3 675B Instruct costs $0.5/1M input and $1.5/1M output tokens. Nemotron-Nano-9B-v2 costs $0.04/1M input and $0.16/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Mistral Large 3 675B Instruct or Nemotron-Nano-9B-v2 open source?
Mistral Large 3 675B Instruct is listed under 1. Nemotron-Nano-9B-v2 is listed under Unknown. 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, Mistral Large 3 675B Instruct or Nemotron-Nano-9B-v2?
Both Mistral Large 3 675B Instruct and Nemotron-Nano-9B-v2 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 Mistral Large 3 675B Instruct and Nemotron-Nano-9B-v2?
Mistral Large 3 675B Instruct is available on AWS Bedrock, NVIDIA NIM, Mistral AI Studio, and Microsoft Foundry. Nemotron-Nano-9B-v2 is available on NVIDIA NIM and OpenRouter. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
When should I pick Mistral Large 3 675B Instruct over Nemotron-Nano-9B-v2?
Nemotron-Nano-9B-v2 is ~1150% cheaper at $0.04/1M; pay for Mistral Large 3 675B Instruct only for provider fit. If your workload also depends on provider fit, start with Mistral Large 3 675B Instruct; if it depends on provider fit, run the same evaluation with Nemotron-Nano-9B-v2.
Continue comparing
Last reviewed: 2026-05-19. Data sourced from public model cards and provider documentation.