Mistral 3 logoMistral 3
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Mistral Medium 3.5 logoMistral Medium 3.5

Mistral 3 vs Mistral Medium 3.5: Which is Better in 2026?

A comprehensive comparison of Mistral 3 and Mistral Medium 3.5 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 Medium 3.5 if:

  • You want more affordable paid plans (from $1.5/mo)
  • You need a broader feature set (9 features vs 8)
  • You need 128b dense model (merged: instruction-following + reasoning + coding) or 256k token context window

Mistral 3 vs Mistral Medium 3.5: At a Glance

Attribute
Mistral 3
Mistral Medium 3.5
Pricing Model
Freemium
Freemium
Starting Price
Apache 2.0 open weights — free to download and self-host. Available via Mistral API (pricing on mistral.ai/pricing). Accessible on Le Chat free and Pro plans.
Starting at $1.5/month
Free Tier
✓ Yes
✓ Yes
Category
llm-apis
llm-apis
Features Count
8 features
9 features
Shared Features
0 features in common

Pricing Comparison: Mistral 3 vs Mistral Medium 3.5

Understanding the pricing differences between Mistral 3 and Mistral Medium 3.5 is crucial for making the right choice. Here's how their plans compare side by side.

Mistral 3 Pricing

Accessible on Le Chat free and Pro plans.See website
View full Mistral 3 pricing →

Mistral Medium 3.5 Pricing

API:$1.5/month
Starter$7.5/month
View full Mistral Medium 3.5 pricing →

💡 Pricing takeaway: Both Mistral 3 and Mistral Medium 3.5 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 Medium 3.5 stacks up.

Feature
Mistral 3
Mistral Medium 3.5
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
128B dense model (merged: instruction-following + reasoning + coding)
256k token context window
77.6% on SWE-Bench Verified (beats Devstral 2 and Qwen3.5 397B A17B)
91.4 on τ³-Telecom (strong agentic capabilities)
Configurable reasoning effort per request
Vision encoder trained from scratch — handles variable image sizes and aspect ratios
Open weights under modified MIT license (self-hostable on 4 GPUs)
Powers Mistral Vibe remote coding agents and Le Chat Work mode
Async cloud coding sessions with GitHub, Linear, Jira, Sentry integrations

What Makes Each Tool Unique

🔵 Unique to Mistral 3

Features available in Mistral 3 but not in Mistral Medium 3.5:

  • 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 Medium 3.5

Features available in Mistral Medium 3.5 but not in Mistral 3:

  • 128B dense model (merged: instruction-following + reasoning + coding)
  • 256k token context window
  • 77.6% on SWE-Bench Verified (beats Devstral 2 and Qwen3.5 397B A17B)
  • 91.4 on τ³-Telecom (strong agentic capabilities)
  • Configurable reasoning effort per request
  • Vision encoder trained from scratch — handles variable image sizes and aspect ratios
  • Open weights under modified MIT license (self-hostable on 4 GPUs)
  • Powers Mistral Vibe remote coding agents and Le Chat Work mode
  • Async cloud coding sessions with GitHub, Linear, Jira, Sentry integrations

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
Try Mistral 3

Best for: Mistral Medium 3.5

Mistral's first flagship merged model, released May 22, 2026. A dense 128B model with a 256k context window that handles instruction-following, reasoning, and coding in a single set of weights. Available as open weights (modified MIT license) and powers Mistral Vibe remote coding agents and Le Chat's new Work mode. SWE-Bench Verified: 77.6%. API: $1.5/M input, $7.5/M output.

Ideal use cases:

  • Teams or individuals who need 128b dense model (merged: instruction-following + reasoning + coding)
  • Teams or individuals who need 256k token context window
  • Teams or individuals who need 77.6% on swe-bench verified (beats devstral 2 and qwen3.5 397b a17b)
  • Teams or individuals who need 91.4 on τ³-telecom (strong agentic capabilities)
  • Anyone focused on mistral workflows
  • Anyone focused on llm workflows
Try Mistral Medium 3.5

🔧 Other llm-apis Tools to Consider

Mistral 3 and Mistral Medium 3.5 aren't the only options. Here are other popular tools in the same space:

Frequently Asked Questions

Is Mistral 3 better than Mistral Medium 3.5?

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 Medium 3.5 provides 9 features including 128B dense model (merged: instruction-following + reasoning + coding) and 256k token context window. Mistral 3 uses a freemium model with a free tier, while Mistral Medium 3.5 is freemium with free access available. Choose based on which features and pricing model align with your requirements.

Is Mistral 3 cheaper than Mistral Medium 3.5?

Mistral 3 doesn't have standard paid plans, while Mistral Medium 3.5 starts at $1.5/month. 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 Medium 3.5 together?

Yes, many users combine Mistral 3 and Mistral Medium 3.5 in their workflow. Mistral 3 excels at mistral large 3: sparse moe with 41b active / 675b total parameters, while Mistral Medium 3.5 shines with 128b dense model (merged: instruction-following + reasoning + coding). 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 Medium 3.5?

While both are llm-apis tools, Mistral 3 emphasizes mistral large 3: sparse moe with 41b active / 675b total parameters, whereas Mistral Medium 3.5 is known for 128b dense model (merged: instruction-following + reasoning + coding). The best choice depends on your specific workflow and feature priorities.

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