Mistral Small 4 vs North Mini Code: Which is Better in 2026?
A comprehensive comparison of Mistral Small 4 and North Mini Code covering features, pricing, use cases, and which tool is the right choice for your needs.
⚡ Quick Verdict
Choose Mistral Small 4 if:
- →You need a broader feature set (10 features vs 9)
- →You need 119b total parameters, 6b active per token (moe: 128 experts, 4 active) or 256k token context window
Choose North Mini Code if:
- →You want more affordable paid plans (from $2/mo)
- →You need 30b total / 3b active moe architecture — dense-model quality at fraction of inference cost or 2.8× higher output throughput than devstral small 2 (identical hardware)
Mistral Small 4 vs North Mini Code: At a Glance
Pricing Comparison: Mistral Small 4 vs North Mini Code
Understanding the pricing differences between Mistral Small 4 and North Mini Code is crucial for making the right choice. Here's how their plans compare side by side.
Mistral Small 4 Pricing
North Mini Code Pricing
💡 Pricing takeaway: Both Mistral Small 4 and North Mini Code 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 Small 4 and North Mini Code stacks up.
What Makes Each Tool Unique
🔵 Unique to Mistral Small 4
Features available in Mistral Small 4 but not in North Mini Code:
- ✓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
🟣 Unique to North Mini Code
Features available in North Mini Code but not in Mistral Small 4:
- ✓30B total / 3B active MoE architecture — dense-model quality at fraction of inference cost
- ✓2.8× higher output throughput than Devstral Small 2 (identical hardware)
- ✓30% better inter-token latency than Devstral Small 2
- ✓33.4 on Artificial Analysis Coding Index
- ✓256K total context window; 64K max generation
- ✓Apache 2.0 license — fully open for commercial use, modification, and redistribution
- ✓Single H100 @ FP8 minimum — unusually accessible for a 30B model
- ✓Optimized for code generation, agentic software engineering, and terminal tasks
- ✓Available on Hugging Face, Cohere API, Model Vault, OpenRouter, and OpenCode
Use Case Recommendations
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
Best for: North Mini Code
Cohere's first agentic coding model and inaugural member of the North model family. A 30B Mixture of Experts model with only 3B active parameters per token, released June 9, 2026 under Apache 2.0. Achieves 2.8× higher output throughput than Devstral Small 2 on identical hardware, 256K context, and runs on a single H100 at FP8.
Ideal use cases:
- •Teams or individuals who need 30b total / 3b active moe architecture — dense-model quality at fraction of inference cost
- •Teams or individuals who need 2.8× higher output throughput than devstral small 2 (identical hardware)
- •Teams or individuals who need 30% better inter-token latency than devstral small 2
- •Teams or individuals who need 33.4 on artificial analysis coding index
- •Anyone focused on cohere workflows
- •Anyone focused on llm workflows
🔧 Other llm-apis Tools to Consider
Mistral Small 4 and North Mini Code 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
Mistral 3
Mistral's MoE flagship + edge model family — Apache 2.0, multimodal, reasoning
Codestral 25.08
Mistral's low-latency code completion model — FIM, 80+ languages, 256k context
Frequently Asked Questions
Is Mistral Small 4 better than North Mini Code?
It depends on your needs. Mistral Small 4 offers 10 key features including 119B total parameters, 6B active per token (MoE: 128 experts, 4 active) and 256k token context window, while North Mini Code provides 9 features including 30B total / 3B active MoE architecture — dense-model quality at fraction of inference cost and 2.8× higher output throughput than Devstral Small 2 (identical hardware). Mistral Small 4 uses a freemium model with a free tier, while North Mini Code is freemium with free access available. Choose based on which features and pricing model align with your requirements.
Is Mistral Small 4 cheaper than North Mini Code?
Mistral Small 4 doesn't have standard paid plans, while North Mini Code starts at Apache 2.0 open weights — free to download and self-host from Hugging Face. Available via Cohere API (pay-per-token), Cohere Model Vault (dedicated managed inference), and OpenRouter. Minimum hardware: 1× H100 @ FP8.. 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 Small 4 and North Mini Code together?
Yes, many users combine Mistral Small 4 and North Mini Code in their workflow. Mistral Small 4 excels at 119b total parameters, 6b active per token (moe: 128 experts, 4 active), while North Mini Code shines with 30b total / 3b active moe architecture — dense-model quality at fraction of inference cost. 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 Small 4 and North Mini Code?
While both are llm-apis tools, Mistral Small 4 emphasizes 119b total parameters, 6b active per token (moe: 128 experts, 4 active), whereas North Mini Code is known for 30b total / 3b active moe architecture — dense-model quality at fraction of inference cost. The best choice depends on your specific workflow and feature priorities.