Llama 3.1 NemoGuard 8B Topic Control vs Mistral Small 3.1 24B Instruct
Llama 3.1 NemoGuard 8B Topic Control (2025) and Mistral Small 3.1 24B Instruct (2025) are compact production models from NVIDIA AI and MistralAI. Llama 3.1 NemoGuard 8B Topic Control ships a 4k-token context window, while Mistral Small 3.1 24B 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 Small 3.1 24B Instruct fits 32x more tokens; pick it for long-context work and Llama 3.1 NemoGuard 8B Topic Control for tighter calls.
Decision scorecard
Local evidence first| Signal | Llama 3.1 NemoGuard 8B Topic Control | Mistral Small 3.1 24B Instruct |
|---|---|---|
| Best for | general production evaluation | multimodal apps and provider-routed production |
| Decision fit | Classification | RAG, Long context, and Vision |
| Context window | 4k | 128k |
| Cheapest output | - | $0.30/1M tokens |
| Provider routes | 1 tracked | 6 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Local decision data tags Llama 3.1 NemoGuard 8B Topic Control for Classification.
- Mistral Small 3.1 24B Instruct has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Mistral Small 3.1 24B Instruct has broader tracked provider coverage for fallback and procurement flexibility.
- Mistral Small 3.1 24B Instruct uniquely exposes Vision, Multimodal, and Structured outputs in local model data.
- Local decision data tags Mistral Small 3.1 24B Instruct for RAG, Long context, and Vision.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
Llama 3.1 NemoGuard 8B Topic Control
Unavailable
No complete token price in local provider data
Mistral Small 3.1 24B Instruct
$155
Cheapest tracked route/tier: Together AI
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 3.1 24B 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 | 2025-01-01 | 2025-12-15 |
| Context window | 4k | 128k |
| Parameters | 8B | 24B |
| Architecture | decoder only | dense |
| License | Open Weights | Apache 2.0(OSI) |
| Openness | Open weights | Open source |
| Commercial use | - | Commercial use allowed |
| Knowledge cutoff | - | 2023-10 |
Pricing and availability
| Pricing attribute | Llama 3.1 NemoGuard 8B Topic Control | Mistral Small 3.1 24B Instruct |
|---|---|---|
| Input price | - | $0.10/1M tokens |
| Output price | - | $0.30/1M tokens |
| Providers |
Capabilities
| Capability | Llama 3.1 NemoGuard 8B Topic Control | Mistral Small 3.1 24B 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 rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on vision: Mistral Small 3.1 24B Instruct, multimodal input: Mistral Small 3.1 24B Instruct, and structured outputs: Mistral Small 3.1 24B 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 NemoGuard 8B Topic Control has no token price sourced yet and Mistral Small 3.1 24B Instruct has $0.10/1M 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 NemoGuard 8B Topic Control when provider fit are central to the workload. Choose Mistral Small 3.1 24B 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 NemoGuard 8B Topic Control or Mistral Small 3.1 24B Instruct?
Mistral Small 3.1 24B Instruct supports 128k tokens, while Llama 3.1 NemoGuard 8B Topic Control 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 NemoGuard 8B Topic Control or Mistral Small 3.1 24B Instruct open source?
Llama 3.1 NemoGuard 8B Topic Control is listed under Open Weights. Mistral Small 3.1 24B 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 NemoGuard 8B Topic Control or Mistral Small 3.1 24B Instruct?
Mistral Small 3.1 24B 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 NemoGuard 8B Topic Control or Mistral Small 3.1 24B Instruct?
Mistral Small 3.1 24B 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 NemoGuard 8B Topic Control or Mistral Small 3.1 24B Instruct?
Mistral Small 3.1 24B 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 NemoGuard 8B Topic Control and Mistral Small 3.1 24B Instruct?
Llama 3.1 NemoGuard 8B Topic Control is available on NVIDIA NIM. Mistral Small 3.1 24B Instruct is available on Cloudflare Workers AI, OpenRouter, Fireworks AI, NVIDIA NIM, and Together AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Last reviewed: 2026-05-11. Data sourced from public model cards and provider documentation.