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Codestral 2508 vs Gemini 3.1 Pro

How do these models stack up? Below is an expert side-by-side comparison of specifications, context window capacity, live pricing per million tokens, and standardized benchmark scores for Codestral 2508 and Gemini 3.1 Pro.

Mistral

Codestral 2508

Mistral's cutting-edge language model for coding released end of July 2025. Codestral specializes in low-latency, high-frequency tasks such as fill-in-the-middle (FIM), code correction and test generation. [Blog Post](https://mistral.ai/news/codestral-25-08)

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Google

Gemini 3.1 Pro

Google's premiere multi-modal model featuring a massive 2 million token context window. Engineered for deep code analysis, video indexing, and long-context reasoning.

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Technical Specifications

SpecificationCodestral 2508Gemini 3.1 Pro
ProviderMistralGoogle
Context Window256,000 tokens2,000,000 tokens
Agent SuitabilityN/A93/100
Time to First Token (TTFT)N/A420 ms
Deployment Modelself hostablemanaged api
Production Stabilitystablestable
API AvailableYesYes
Released Date2025-08-012026-04-20

API Pricing Comparison

Input Price per Million Tokens

Codestral 2508

$0.30

Gemini 3.1 Pro

$2.00

Output Price per Million Tokens

Codestral 2508

$0.90

Gemini 3.1 Pro

$12.00

Want to test both models live?

Run side-by-side prompt prompts in our dynamic Sandbox. Check execution speeds, latency metrics, and compute actual costs in real-time.

Benchmark Performance Metrics

Scores show the raw performance percentages verified across key evaluation suites. Higher bars indicate superior accuracy and capability in that domain.

MMLUGeneral knowledge & multi-task understanding
N/Avs9280.0%
Codestral 2508
Gemini 3.1 Pro
HumanEvalPython coding & logic synthesis
N/Avs9460.0%
Codestral 2508
Gemini 3.1 Pro
MATHComplex mathematical problem solving
N/Avs8800.0%
Codestral 2508
Gemini 3.1 Pro
GPQAGraduate-level expert reasoning
N/Avs8130.0%
Codestral 2508
Gemini 3.1 Pro
HellaSwagCommonsense reasoning and inference
N/Avs9840.0%
Codestral 2508
Gemini 3.1 Pro
MT-BenchMulti-turn conversation flow quality
N/Avs950.0%
Codestral 2508
Gemini 3.1 Pro

Codestral 2508 Quirks & Gotchas

No developer gotchas reported.

Gemini 3.1 Pro Quirks & Gotchas

  • โ–ธBest model for massive context โ€” 2M token window is class-leading
  • โ–ธTool calling requires explicit schema definition in Google AI Studio