Mistral 7B v0.1 vs Mistral Small 4
Mistral 7B v0.1 (2023) and Mistral Small 4 (2026) are compact production models from MistralAI. Mistral 7B v0.1 ships a 8K-token context window, while Mistral Small 4 ships a 256K-token context window. On pricing, Mistral 7B v0.1 costs $0.05/1M input tokens versus $0.15/1M 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.
Mistral 7B v0.1 is ~200% cheaper at $0.05/1M; pay for Mistral Small 4 only for long-context analysis.
Decision scorecard
Local evidence first| Signal | Mistral 7B v0.1 | Mistral Small 4 |
|---|---|---|
| Decision fit | General | RAG, Agents, and Long context |
| Context window | 8K | 256K |
| Cheapest output | $0.15/1M tokens | $0.6/1M tokens |
| Provider routes | 16 tracked | 3 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Mistral 7B v0.1 has the lower cheapest tracked output price at $0.15/1M tokens.
- Mistral 7B v0.1 has broader tracked provider coverage for fallback and procurement flexibility.
- Mistral Small 4 has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Mistral Small 4 uniquely exposes Vision, Multimodal, and Function calling 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.
Mistral 7B v0.1
$77.50
Cheapest tracked route: DeepInfra
Mistral Small 4
$270
Cheapest tracked route: OpenRouter
Estimated monthly gap: $193. Batch, cache, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on NVIDIA NIM and Mistral AI Studio; start route-level A/B tests there.
- Mistral Small 4 is $0.45/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Mistral Small 4 adds Vision, Multimodal, and Function calling in local capability data.
- Provider overlap exists on Mistral AI Studio and NVIDIA NIM; start route-level A/B tests there.
- Mistral 7B v0.1 is $0.45/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Vision, Multimodal, and Function calling before moving production traffic.
Specs
| Specification | ||
|---|---|---|
| Released | 2023-09-27 | 2026-03-16 |
| Context window | 8K | 256K |
| Parameters | 7B | 119B (6.5B active) |
| Architecture | decoder only | moe |
| License | Apache 2.0 | Apache 2.0 |
| Knowledge cutoff | 2023-12 | 2025-06 |
Pricing and availability
| Pricing attribute | Mistral 7B v0.1 | Mistral Small 4 |
|---|---|---|
| Input price | $0.05/1M tokens | $0.15/1M tokens |
| Output price | $0.15/1M tokens | $0.6/1M tokens |
| Providers |
Capabilities
| Capability | Mistral 7B v0.1 | Mistral Small 4 |
|---|---|---|
| Vision | No | Yes |
| Multimodal | No | 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 vision: Mistral Small 4, multimodal input: Mistral Small 4, function calling: Mistral Small 4, and tool use: Mistral Small 4. 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.
For cost, Mistral 7B v0.1 lists $0.05/1M input and $0.15/1M output tokens, while Mistral Small 4 lists $0.15/1M input and $0.6/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Mistral 7B v0.1 lower by about $0.2 per million blended tokens. Availability is 16 providers versus 3, so concentration risk also matters.
Choose Mistral 7B v0.1 when provider fit, lower input-token cost, and broader provider choice are central to the workload. Choose Mistral Small 4 when long-context analysis and larger context windows 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, Mistral 7B v0.1 or Mistral Small 4?
Mistral Small 4 supports 256K tokens, while Mistral 7B v0.1 supports 8K tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Which is cheaper, Mistral 7B v0.1 or Mistral Small 4?
Mistral 7B v0.1 is cheaper on tracked token pricing. Mistral 7B v0.1 costs $0.05/1M input and $0.15/1M output tokens. Mistral Small 4 costs $0.15/1M input and $0.6/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Mistral 7B v0.1 or Mistral Small 4 open source?
Mistral 7B v0.1 is listed under Apache 2.0. 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, Mistral 7B v0.1 or Mistral Small 4?
Mistral Small 4 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, Mistral 7B v0.1 or Mistral Small 4?
Mistral Small 4 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 Mistral 7B v0.1 and Mistral Small 4?
Mistral 7B v0.1 is available on GCP Vertex AI, OctoAI API (Deprecated), DeepInfra, Mistral AI Studio, and Baseten API. 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.
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Last reviewed: 2026-05-16. Data sourced from public model cards and provider documentation.