Llama 3.1 Nemotron Nano VL 8B v1 vs Mistral Small 4
Llama 3.1 Nemotron Nano VL 8B v1 (2025) and Mistral Small 4 (2026) are compact production models from NVIDIA AI and MistralAI. Llama 3.1 Nemotron Nano VL 8B v1 ships a 4K-token context window, while Mistral Small 4 ships a 256K-token context window. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit. It focuses on practical selection signals rather than broad model-family marketing.
Mistral Small 4 fits 64x more tokens; pick it for long-context work and Llama 3.1 Nemotron Nano VL 8B v1 for tighter calls.
Decision scorecard
Local evidence first| Signal | Llama 3.1 Nemotron Nano VL 8B v1 | Mistral Small 4 |
|---|---|---|
| Decision fit | Vision | RAG, Agents, and Long context |
| Context window | 4K | 256K |
| Cheapest output | - | $0.6/1M tokens |
| Provider routes | 1 tracked | 3 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Local decision data tags Llama 3.1 Nemotron Nano VL 8B v1 for Vision.
- Mistral Small 4 has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Mistral Small 4 has broader tracked provider coverage for fallback and procurement flexibility.
- Mistral Small 4 uniquely exposes Function calling and Tool use in local model data.
- Local decision data tags Mistral Small 4 for RAG, Agents, and Long context.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output prices on this page.
Llama 3.1 Nemotron Nano VL 8B v1
Unavailable
No complete token price in local provider data
Mistral Small 4
$270
Cheapest tracked route: 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 Small 4 adds Function calling and Tool use in local capability data.
- Provider overlap exists on NVIDIA NIM; start route-level A/B tests there.
- Check replacement coverage for Function calling and Tool use before moving production traffic.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-03-01 | 2026-03-16 |
| Context window | 4K | 256K |
| Parameters | 8B | 119B (6.5B active) |
| Architecture | decoder only | moe |
| License | 1 | Apache 2.0 |
| Knowledge cutoff | - | 2025-06 |
Pricing and availability
| Pricing attribute | Llama 3.1 Nemotron Nano VL 8B v1 | Mistral Small 4 |
|---|---|---|
| Input price | - | $0.15/1M tokens |
| Output price | - | $0.6/1M tokens |
| Providers |
Capabilities
| Capability | Llama 3.1 Nemotron Nano VL 8B v1 | Mistral Small 4 |
|---|---|---|
| Vision | Yes | Yes |
| Multimodal | Yes | Yes |
| Reasoning | No | No |
| Function calling | No | Yes |
| Tool use | No | Yes |
| Structured outputs | No | No |
| Code execution | No | No |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on function calling: Mistral Small 4 and tool use: Mistral Small 4. Both models share vision and multimodal input, 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 VL 8B v1 has no token price sourced yet and Mistral Small 4 has $0.15/1M input tokens. Provider availability is 1 tracked routes versus 3. 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 VL 8B v1 when vision-heavy evaluation are central to the workload. Choose Mistral Small 4 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. It also helps separate model capability from provider packaging, which can change cost and latency.
FAQ
Which has a larger context window, Llama 3.1 Nemotron Nano VL 8B v1 or Mistral Small 4?
Mistral Small 4 supports 256K tokens, while Llama 3.1 Nemotron Nano VL 8B v1 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 VL 8B v1 or Mistral Small 4 open source?
Llama 3.1 Nemotron Nano VL 8B v1 is listed under 1. Mistral Small 4 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 VL 8B v1 or Mistral Small 4?
Both Llama 3.1 Nemotron Nano VL 8B v1 and Mistral Small 4 expose vision. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface.
Which is better for multimodal input, Llama 3.1 Nemotron Nano VL 8B v1 or Mistral Small 4?
Both Llama 3.1 Nemotron Nano VL 8B v1 and Mistral Small 4 expose multimodal input. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface.
Which is better for function calling, Llama 3.1 Nemotron Nano VL 8B v1 or Mistral Small 4?
Mistral Small 4 has the clearer documented function calling signal in this comparison. If function calling 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 VL 8B v1 and Mistral Small 4?
Llama 3.1 Nemotron Nano VL 8B v1 is available on NVIDIA NIM. Mistral Small 4 is available on OpenRouter, NVIDIA NIM, and Mistral AI Studio. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Last reviewed: 2026-05-14. Data sourced from public model cards and provider documentation.