Mistral 3 vs Mistral Small 4: Which is Better in 2026?
A comprehensive comparison of Mistral 3 and Mistral Small 4 covering features, pricing, use cases, and which tool is the right choice for your needs.
⚡ Quick Verdict
Choose Mistral 3 if:
- →You need mistral large 3: sparse moe with 41b active / 675b total parameters or ministral 3 series: dense 3b, 8b, 14b models optimized for edge inference
Choose Mistral Small 4 if:
- →You need a broader feature set (10 features vs 8)
- →You need 119b total parameters, 6b active per token (moe: 128 experts, 4 active) or 256k token context window
Mistral 3 vs Mistral Small 4: At a Glance
Pricing Comparison: Mistral 3 vs Mistral Small 4
Understanding the pricing differences between Mistral 3 and Mistral Small 4 is crucial for making the right choice. Here's how their plans compare side by side.
Mistral Small 4 Pricing
💡 Pricing takeaway: Both Mistral 3 and Mistral Small 4 offer free tiers, making it easy to try before you buy. Compare the specific plans to find the best value for your use case.
Feature-by-Feature Comparison
Here's how every feature from Mistral 3 and Mistral Small 4 stacks up.
What Makes Each Tool Unique
🔵 Unique to Mistral 3
Features available in Mistral 3 but not in Mistral Small 4:
- ✓Mistral Large 3: sparse MoE with 41B active / 675B total parameters
- ✓Ministral 3 series: dense 3B, 8B, 14B models optimized for edge inference
- ✓Ministral variants include base, instruct, and reasoning variants
- ✓Image understanding across 40+ languages (Ministral 14B)
- ✓Ministral 14B reasoning: 85% on AIME '25
- ✓Mistral Large 3 ranks #2 OSS non-reasoning on LMArena leaderboard
- ✓All models released under Apache 2.0 license
- ✓First Mistral MoE model since the seminal Mixtral series
🟣 Unique to Mistral Small 4
Features available in Mistral Small 4 but not in Mistral 3:
- ✓119B total parameters, 6B active per token (MoE: 128 experts, 4 active)
- ✓256k token context window
- ✓Unified reasoning, vision, and coding in a single model
- ✓Configurable reasoning effort: reasoning_effort='none' (fast) or 'high' (deep)
- ✓Native image input support (text + vision in one model)
- ✓Apache 2.0 license — permissive commercial use, no additional restrictions
- ✓40% reduction in end-to-end latency vs Mistral Small 3
- ✓3× higher throughput vs Mistral Small 3 (throughput-optimized setup)
- ✓Beats GPT-OSS 120B on AA LCR and LiveCodeBench with shorter outputs
- ✓Runs on vLLM, llama.cpp, SGLang, and Transformers
Use Case Recommendations
Best for: Mistral 3
Mistral's December 2025 model family: Mistral Large 3 (flagship sparse MoE, 41B active / 675B total parameters, Apache 2.0) plus the Ministral 3 series (dense 3B, 8B, 14B edge models). Mistral Large 3 is Mistral's first MoE since Mixtral, with multimodal capabilities and #2 ranking on LMArena for OSS non-reasoning models. Ministral 14B reasoning variant scores 85% on AIME '25. All released under Apache 2.0.
Ideal use cases:
- •Teams or individuals who need mistral large 3: sparse moe with 41b active / 675b total parameters
- •Teams or individuals who need ministral 3 series: dense 3b, 8b, 14b models optimized for edge inference
- •Teams or individuals who need ministral variants include base, instruct, and reasoning variants
- •Teams or individuals who need image understanding across 40+ languages (ministral 14b)
- •Anyone focused on mistral workflows
- •Anyone focused on llm workflows
Best for: Mistral Small 4
Mistral's first unified open-source model, released March 16, 2026. A 119B MoE model (6B active parameters per token) that merges reasoning (Magistral), multimodal vision (Pixtral), and agentic coding (Devstral) into a single Apache 2.0 model. 256k context window. 40% faster and 3× higher throughput than Mistral Small 3. Beats GPT-OSS 120B on coding and reasoning benchmarks while generating shorter outputs.
Ideal use cases:
- •Teams or individuals who need 119b total parameters, 6b active per token (moe: 128 experts, 4 active)
- •Teams or individuals who need 256k token context window
- •Teams or individuals who need unified reasoning, vision, and coding in a single model
- •Teams or individuals who need configurable reasoning effort: reasoning_effort='none' (fast) or 'high' (deep)
- •Anyone focused on mistral workflows
- •Anyone focused on llm workflows
🔧 Other llm-apis Tools to Consider
Mistral 3 and Mistral Small 4 aren't the only options. Here are other popular tools in the same space:
Claude Opus 4.8
Anthropic's flagship model — stronger coding, agents, and honesty
Mistral Medium 3.5
Mistral's 128B merged flagship — open weights, coding+reasoning+instructions
North Mini Code
Cohere's open-source agentic coding model — 30B MoE, 3B active, Apache 2.0
Codestral 25.08
Mistral's low-latency code completion model — FIM, 80+ languages, 256k context
Frequently Asked Questions
Is Mistral 3 better than Mistral Small 4?
It depends on your needs. Mistral 3 offers 8 key features including Mistral Large 3: sparse MoE with 41B active / 675B total parameters and Ministral 3 series: dense 3B, 8B, 14B models optimized for edge inference, while Mistral Small 4 provides 10 features including 119B total parameters, 6B active per token (MoE: 128 experts, 4 active) and 256k token context window. Mistral 3 uses a freemium model with a free tier, while Mistral Small 4 is freemium with free access available. Choose based on which features and pricing model align with your requirements.
Is Mistral 3 cheaper than Mistral Small 4?
Both tools have similar pricing structures. Both tools offer free tiers, so you can try each before committing. Always check the official websites for the most current pricing.
Can I use Mistral 3 and Mistral Small 4 together?
Yes, many users combine Mistral 3 and Mistral Small 4 in their workflow. Mistral 3 excels at mistral large 3: sparse moe with 41b active / 675b total parameters, while Mistral Small 4 shines with 119b total parameters, 6b active per token (moe: 128 experts, 4 active). Using both allows you to leverage the strengths of each tool, though this means managing two subscriptions — though free tiers can help manage costs.
What's the main difference between Mistral 3 and Mistral Small 4?
While both are llm-apis tools, Mistral 3 emphasizes mistral large 3: sparse moe with 41b active / 675b total parameters, whereas Mistral Small 4 is known for 119b total parameters, 6b active per token (moe: 128 experts, 4 active). The best choice depends on your specific workflow and feature priorities.