Mistral AIMistral Small 4VSOpenAIGPT-5.5

Analysis by:the whichllmmodel Editorial Team|Updated: June 2026

Our Take

We recommend GPT-5.5 if you need peak intelligence for complex complex codebases, multi-file repositories, and architectural planning, or the 42.9x cheaper Mistral Small 4 if your workflow is limited to scripting single-file apps or clearly defined functions. While GPT-5.5 holds a major reasoning advantage, Mistral Small 4 is optimized for high-volume budget pipelines. Choose GPT-5.5 for architectural codebase planning, or Mistral Small 4 to maximize your budget for basic scripts.

▶WHY?

Benchmark Calculations & Evidence:

Coding Evaluation: Mistral Small 4 was evaluated on LiveCodeBench (scoring 63.6%), while GPT-5.5 was evaluated on SWE-bench Pro (scoring 58.6%).

Reasoning Accuracy: Both models were evaluated on the GPQA Diamond benchmark. GPT-5.5 scored 93.6%, while Mistral Small 4 scored 71.2%.

Cost Efficiency: Mistral Small 4 pricing ($0.15/M input, $0.6/M output) is 42.9x cheaper than GPT-5.5 ($5/M input, $30/M output).

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Model Specs

Mistral Small 4

Open SourceAPI Available

Website 🤗HF

Benchmarks & Scores

Coding (live-code-bench)

63.6%

scripting single-file apps or clearly defined functions

Reasoning (gpqa-diamond)

71.2%

graduate-level science QA

Cost & Context

Cost (per 1M tokens)42.9x cheaper

$0.26Input: $0.15 | Output: $0.60

Context Window

262.14k tokens

Model Specs

GPT-5.5

Website

Benchmarks & Scores

Coding (swe-bench-pro)

58.6%

complex codebases, multi-file repositories, and architectural planning

Reasoning (gpqa-diamond)Winner (+22.4%)

93.6%

graduate-level science QA

Cost & Context

Cost (per 1M tokens)

$11.25Input: $5.00 | Output: $30.00

Context WindowLarger

1.05M tokens

Read our data collection methodology

Frequently Asked Questions about Mistral Small 4 vs GPT-5.5

Mistral Small 4 is cheaper than GPT-5.5. Mistral Small 4 has a blended cost of $0.26/1M tokens, which is about 42.9x cheaper than GPT-5.5 at $11.25/1M tokens.

For coding tasks, Mistral Small 4 scores 63.6% on live-code-bench (scripting single-file apps or clearly defined functions), while GPT-5.5 scores 58.6% on swe-bench-pro (complex codebases, multi-file repositories, and architectural planning).

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