Model comparison
Codestral vs Gemini 2.5 Pro
Gemini 2.5 Pro is the stronger model overall, scoring 45.0 to 30.6 on the Noometry Index. Codestral costs 7.6× less per token, which makes it the better buy when Gemini 2.5 Pro's lead doesn't matter for your workload.
Last verified . 3 shared benchmarks.
Mistral AI
GoogleSummary
- They share 3 benchmarks with published results for both. Codestral scores higher in 0 categories and Gemini 2.5 Pro in 2 categories; 2 gaps are clear of the uncertainty.
- The widest gap is in coding, where Gemini 2.5 Pro leads 42.4 to 27.3.
- The biggest single-benchmark swing is Aider Polyglot: 11.1% for Codestral and 83.1% for Gemini 2.5 Pro.
- Codestral is cheaper at $0.30 / $0.90 per million input/output tokens, against $1.25 / $10 for Gemini 2.5 Pro.
- Gemini 2.5 Pro accepts more context: 1.05M tokens versus 256K.
Side by side
| Codestral | Gemini 2.5 Pro | |
|---|---|---|
| Provider | Mistral AI | |
| Noometry Index | 30.6 | 45.0 |
| Released | 2024-05-29 | 2025-03-25 |
| Weights | Proprietary | Proprietary |
| Context window | 256K | 1.05M |
| Max output | 8K | 66K |
| Input $ / M tokens | $0.30 | $1.25 |
| Output $ / M tokens | $0.90 | $10 |
| Results tracked | 7 | 78 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding Gemini 2.5 Pro leads
Codestral: 27.3 (#321), Gemini 2.5 Pro: 42.4 (#101)
| Benchmark | Codestral | Gemini 2.5 Pro |
|---|---|---|
| Aider Polyglot | 11.1% | 83.1% |
| ALE-Bench | 137.78 | 785.52 |
| SWE-bench Verified | — | 57.6% |
| SWE-bench Verified (bash only) | — | 53.6% |
| LMArena WebDev | — | 1227 |
| SciCode | — | 42.8% |
| GSO | — | 3.9% |
| WeirdML | — | 54% |
| BigCodeBench Instruct | 41.8% | — |
| LiveBench Coding | — | 85.9% |
| LMArena Coding | — | 1452 |
| BigCodeBench Complete | 52.5% | — |
| CadEval | — | 64% |
| AlgoTune | — | 1.51 |
| HumanEval+ | 73.8% | — |
| MBPP+ | 61.9% | — |
Agentic & Tool Use Not comparable
Codestral: —, Gemini 2.5 Pro: 29.2 (#88)
| Benchmark | Codestral | Gemini 2.5 Pro |
|---|---|---|
| Terminal-Bench | — | 32.6% |
| GDPval | — | 23.3% |
| Remote Labor Index | — | 0.8% |
| TheAgentCompany | — | 30.3% |
| τ²-bench Banking | — | 13.7% |
| DeepResearch Bench | — | 42.8% |
| BALROG | — | 43.3% |
| LMArena Search | — | 1142 |
| METR Time Horizons | — | 55.4% |
| Vending-Bench 2 | — | 573.64 |
Reasoning Gemini 2.5 Pro leads
Codestral: 19.8 (#251), Gemini 2.5 Pro: 28.8 (#99)
| Benchmark | Codestral | Gemini 2.5 Pro |
|---|---|---|
| Kagi LLM Benchmark | 32.5% | 70.3% |
| ARC-AGI-2 | — | 4.9% |
| SimpleBench | — | 62.4% |
| ARC-AGI-1 | — | 41% |
| CritPt | — | 2% |
| Chess Puzzles | — | 20% |
| EnigmaEval | — | 5.6% |
| LiveBench Reasoning | — | 89.8% |
| LMArena Hard Prompts | — | 1455 |
| DTBench | — | 82.4% |
| LiveBench Data Analysis | — | 79.9% |
| LMCA | — | 34.8% |
| Epoch Capabilities Index | — | 145.32 |
| ForecastBench | — | 61.3 |
| LiveBench | — | 82.3% |
Math Not comparable
Codestral: —, Gemini 2.5 Pro: 32.5 (#213)
| Benchmark | Codestral | Gemini 2.5 Pro |
|---|---|---|
| FrontierMath (Tiers 1-3) | — | 24.6% |
| FrontierMath Tier 4 | — | 0% |
| OTIS Mock AIME 2024-2025 | — | 84.7% |
| Omni-MATH | — | 41.6% |
| LiveBench Math | — | 90.2% |
| LMArena Math | — | 1450 |
| MATH Level 5 | — | 95.9% |
| FrontierMath (Feb 2025 set) | — | 14.1% |
| FrontierMath Tier 4 (v1) | — | 4.2% |
Knowledge Not comparable
Codestral: —, Gemini 2.5 Pro: 56.0 (#46)
| Benchmark | Codestral | Gemini 2.5 Pro |
|---|---|---|
| GPQA Diamond | — | 85.3% |
| Humanity's Last Exam | — | 21.6% |
| MMLU-Pro | — | 86.3% |
| Confabulations | — | 10.6% |
| Vectara Hallucination Rate | — | 7% |
| GPQA (HELM) | — | 74.9% |
| LMArena Expert | — | 1452 |
Multimodal Not comparable
Codestral: —, Gemini 2.5 Pro: 45.2 (#18)
| Benchmark | Codestral | Gemini 2.5 Pro |
|---|---|---|
| LMArena Vision | — | 1263 |
| GeoBench | — | 86% |
| VPCT | — | 48% |
| LMArena Document | — | 1421 |
| SpatialViz-Bench | — | 44.7% |
Multilingual Not comparable
Codestral: —, Gemini 2.5 Pro: 55.3 (#31)
| Benchmark | Codestral | Gemini 2.5 Pro |
|---|---|---|
| LMArena Non-English | — | 1451 |
| LMArena Chinese | — | 1507 |
| LMArena French | — | 1472 |
| LMArena German | — | 1487 |
| LMArena Japanese | — | 1461 |
| LMArena Korean | — | 1434 |
| LMArena Russian | — | 1461 |
| LMArena Spanish | — | 1473 |
Instruction Following Not comparable
Codestral: —, Gemini 2.5 Pro: 75.0 (#75)
| Benchmark | Codestral | Gemini 2.5 Pro |
|---|---|---|
| LiveBench Instruction Following | — | 80.6% |
| IFEval | — | 84% |
| LMArena Instruction Following | — | 1437 |
Long Context Not comparable
Codestral: —, Gemini 2.5 Pro: 59.8 (#5)
| Benchmark | Codestral | Gemini 2.5 Pro |
|---|---|---|
| Fiction.LiveBench | — | 91.7% |
| LMArena Longer Query | — | 1449 |
Writing & Preference Not comparable
Codestral: —, Gemini 2.5 Pro: 63.7 (#62)
| Benchmark | Codestral | Gemini 2.5 Pro |
|---|---|---|
| LMArena Text | — | 1458 |
| LMArena Creative Writing | — | 1454 |
| Short-Story Creative Writing | — | 83.8% |
| EQ-Bench Creative Writing | — | 1421 |
| WildBench | — | 85.7% |
| LMArena Multi-Turn | — | 1453 |
| LiveBench Language | — | 67.8% |
Frequently asked questions
Is Codestral better than Gemini 2.5 Pro?
Gemini 2.5 Pro is the stronger model overall, scoring 45.0 to 30.6 on the Noometry Index. Codestral costs 7.6× less per token, which makes it the better buy when Gemini 2.5 Pro's lead doesn't matter for your workload.
Which is cheaper, Codestral or Gemini 2.5 Pro?
Codestral is cheaper. It lists at $0.30 per million input tokens and $0.90 per million output tokens; Gemini 2.5 Pro lists at $1.25 and $10.
Is Codestral or Gemini 2.5 Pro better for coding?
Gemini 2.5 Pro scores higher on coding benchmarks: 42.4 versus 27.3 in the Noometry coding category.
Which has the bigger context window?
Gemini 2.5 Pro does, with 1.05M tokens against 256K.
How many benchmarks do Codestral and Gemini 2.5 Pro share?
3 benchmarks have published results for both models. Codestral has 7 scored results on Noometry and Gemini 2.5 Pro has 78.