Llama 3.1 Swallow 8B Instruct vs Mistral Medium 3 Instruct
Llama 3.1 Swallow 8B Instruct (2025) and Mistral Medium 3 Instruct (2025) are compact production models from Tokyo Institute of Technology and MistralAI. Llama 3.1 Swallow 8B Instruct ships a 4k-token context window, while Mistral Medium 3 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 Medium 3 Instruct fits 32x more tokens; pick it for long-context work and Llama 3.1 Swallow 8B Instruct for tighter calls.
Decision scorecard
Local evidence first| Signal | Llama 3.1 Swallow 8B Instruct | Mistral Medium 3 Instruct |
|---|---|---|
| Best for | general production evaluation | multimodal apps and provider-routed production |
| Decision fit | General | Long context and Vision |
| Context window | 4k | 128k |
| Cheapest output | - | $2/1M tokens |
| Provider routes | 1 tracked | 2 tracked |
| Shared benchmarks | 0 shared | 0 shared |
Decision tradeoffs
- Use Llama 3.1 Swallow 8B Instruct when your own prompt tests beat the comparison signals; the local data does not show a decisive standalone advantage yet.
- Mistral Medium 3 Instruct has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Mistral Medium 3 Instruct has broader tracked provider coverage for fallback and procurement flexibility.
- Mistral Medium 3 Instruct uniquely exposes Vision and Multimodal in local model data.
- Local decision data tags Mistral Medium 3 Instruct for 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 Swallow 8B Instruct
Unavailable
No complete token price in local provider data
Mistral Medium 3 Instruct
$820
Cheapest tracked route/tier: Mistral AI Studio
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 Medium 3 Instruct adds Vision and Multimodal in local capability data.
- Provider overlap exists on NVIDIA NIM; start route-level A/B tests there.
- Check replacement coverage for Vision and Multimodal before moving production traffic.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-01-01 | 2025-10-01 |
| Context window | 4k | 128k |
| Parameters | 8B | — |
| Architecture | Decoder Only | Decoder Only |
| License | Llama 2 Community | Proprietary |
| Openness | Open weights | Proprietary |
| Commercial use | Commercial use: conditional | Commercial use: conditional |
| Knowledge cutoff | 2023 | 2025-03 |
Pricing and availability
| Pricing attribute | Llama 3.1 Swallow 8B Instruct | Mistral Medium 3 Instruct |
|---|---|---|
| Input price | - | $0.40/1M tokens |
| Output price | - | $2/1M tokens |
| Providers |
Capabilities
| Capability | Llama 3.1 Swallow 8B Instruct | Mistral Medium 3 Instruct |
|---|---|---|
| Vision | No | Yes |
| Multimodal | No | Yes |
| Reasoning | No | No |
| Function calling | No | No |
| Tool use | No | No |
| Structured outputs | No | 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.
Deep dive
The capability footprint differs most on vision: Mistral Medium 3 Instruct and multimodal input: Mistral Medium 3 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 Swallow 8B Instruct has no token price sourced yet and Mistral Medium 3 Instruct has $0.40/1M input tokens. Provider availability is 1 tracked routes versus 2. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.
Choose Llama 3.1 Swallow 8B Instruct when provider fit are central to the workload. Choose Mistral Medium 3 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. 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 Swallow 8B Instruct or Mistral Medium 3 Instruct?
Mistral Medium 3 Instruct supports 128k tokens, while Llama 3.1 Swallow 8B Instruct 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 Swallow 8B Instruct or Mistral Medium 3 Instruct open source?
Llama 3.1 Swallow 8B Instruct is listed under Llama 2 Community. Mistral Medium 3 Instruct is listed under Proprietary. 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 Swallow 8B Instruct or Mistral Medium 3 Instruct?
Mistral Medium 3 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 Swallow 8B Instruct or Mistral Medium 3 Instruct?
Mistral Medium 3 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.
Where can I run Llama 3.1 Swallow 8B Instruct and Mistral Medium 3 Instruct?
Llama 3.1 Swallow 8B Instruct is available on NVIDIA NIM. Mistral Medium 3 Instruct is available on NVIDIA NIM and Mistral AI Studio. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
When should I pick Llama 3.1 Swallow 8B Instruct over Mistral Medium 3 Instruct?
Mistral Medium 3 Instruct fits 32x more tokens; pick it for long-context work and Llama 3.1 Swallow 8B Instruct for tighter calls. If your workload also depends on provider fit, start with Llama 3.1 Swallow 8B Instruct; if it depends on long-context analysis, run the same evaluation with Mistral Medium 3 Instruct.
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Last reviewed: 2026-06-30. Data sourced from public model cards and provider documentation.