Coding · Head-to-head
GPT-5.5 vs North Mini Code
GPT-5.5 vs North Mini Code: pricing, features, and which to pick in 2026.
The verdict
Pick GPT-5.5 if…
- →overall capability matters more than price (AI Score 9.4 vs 8.2)
- →you want our editor's pick for this category
- →your primary use case is developers and teams needing a frontier reasoning model for agentic coding workflows and large-codebase context handling.
Pick North Mini Code if…
- →budget is the constraint
- →your primary use case is developers building self-hosted agentic coding assistants who want a code-specialist open-weights model rather than a general-purpose llm.
Side-by-side specs
| Spec | GPT-5.5 | North Mini Code |
|---|---|---|
| Category | Coding | Coding |
| Pricing model | paid | free |
| Headline pricing | API: $5/$30 per 1M tokens (in/out). ChatGPT Plus $20/mo, Pro $200/mo | Free (open-source, Apache 2.0) |
| Free tier | No free API tier. Free ChatGPT users get GPT-4o, not GPT-5.5. | Completely free and open-source under Apache 2.0. You pay only for your own compute or LLM API hosting costs. |
| AI Score | 9.4/10 | 8.2/10 |
| Best for | Developers and teams needing a frontier reasoning model for agentic coding workflows and large-codebase context handling. | Developers building self-hosted agentic coding assistants who want a code-specialist open-weights model rather than a general-purpose LLM. |
| Editor's pick | ✓ Yes | — |
| Use cases | development agents | development agents |
| Date added | 2026-05-02 | 2026-06-15 |
Pros and cons
GPT-5.5
Coding · paid
Pros
- ✓Top-of-class coding and reasoning benchmarks — measurably ahead of GPT-5 and competitive alternatives
- ✓True agentic capability with tool use, self-correction, and multi-step task completion
- ✓272K context handles entire codebases without chunking workarounds
- ✓Codex integration turns it into an autonomous software engineer inside ChatGPT
Cons
- ×API pricing is premium — $30/M output tokens adds up fast for heavy usage
- ×No free tier for the API; ChatGPT Free users are stuck on GPT-4o
- ×Slower inference than lighter models like GPT-4o-mini for simple tasks
- ×Closed-source with no self-hosting option — full vendor lock-in to OpenAI
North Mini Code
Coding · free
Pros
- ✓Strong SWE-Bench scores (67.6% Verified, 40.2% Pro) from only 3B active parameters — exceptional efficiency
- ✓Apache 2.0 license with 26 quantized variants makes self-hosting on consumer hardware viable
- ✓256K context window with 64K output handles large codebases in a single pass
- ✓Interleaved thinking with native tool use is purpose-built for agentic coding workflows
Cons
- ×Code-specialist only — not a general-purpose model, so don't expect strong performance on non-coding tasks
- ×Requires your own GPU infrastructure or API hosting — no managed cloud endpoint from Cohere yet
- ×Relatively new (June 2026) with limited third-party evaluations beyond the team's own benchmarks
- ×MoE architecture needs compatible serving infrastructure (vLLM, SGLang) — not a simple drop-in for all frameworks
Related comparisons
Updated 2026-06-15. Spec data sourced from official product pages and tracked in our public directory at /tools.