Codestral 25.01 wins on coding (88 vs 72) and price ($0.9 vs $3/1M input) and context window (256K vs 128K). Mistral Large 2 wins on writing quality. For most workflows, Codestral 25.01 is the stronger default — best budget-focused coding specialist for high-volume developer teams.
The shortest way to see the safest default, the lower-cost option, and the specialist pick before you read deeper.
Codestral 25.01 is the safest overall answer here when you want the strongest default instead of the lowest list price.
Switch the scoring lens to see whether the top answer changes when you care more about cost, speed, or long-document work.
Mistral / Balanced / Mar 27, 2026
Best balanced generalist for EU teams with data residency needs.
Ranks models by the broadest mix of coding, writing, research, and long-context usefulness.
You want best-in-class performance for any specific use case — the frontier leaders win.
The fastest way to see where the recommendation shifts when your priority changes.
Great value for code completion and implementation tasks
Faster and much cheaper than premium coding models
Strong fit for engineering teams scaling API usage
Weaker on non-technical writing and nuanced strategy work
Grok 4 now offers stronger coding with a 2M context at only $2/$6
UseRightAI recommendations are based on practical decision factors people actually feel in day-to-day use.
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Codestral 25.01 wins on more categories — coding, budget, reasoning. Mistral Large 2 is the better pick when balanced team usage with eu data residency requirements. The right choice depends on your specific use case.
Codestral 25.01 is cheaper at $0.9/1M input and $2.7/1M output. Mistral Large 2 costs $3/1M input and $9/1M output.
Codestral 25.01 has the larger context window at 256K tokens vs Mistral Large 2's 128K. For large document analysis, Codestral 25.01 is the stronger pick.
Codestral 25.01 is better for coding with a score of 88 vs Mistral Large 2's 72. For the highest coding quality available, Claude Sonnet 4.6 (79.6% SWE-bench) or Opus 4.6 (80.8%) remain benchmarks.
Codestral 25.01 is faster with a very fast speed rating (score: 5) vs Mistral Large 2's balanced rating (score: 3).
Meta: Llama 3.1 8B Instruct is the lower-cost option to start with when you still need useful output at scale.
Mistral Large 2 is the better pick when response speed matters more than maximum reasoning depth.
Codestral 25.01 leads on coding with a score of 88 vs 72 for Mistral Large 2.
Codestral 25.01 has the larger context window: 256K vs 128K for Mistral Large 2.
Codestral 25.01 is cheaper at $0.9/1M input tokens vs $3/1M for Mistral Large 2.
Choose Codestral 25.01 for coding and budget — affordable high-volume coding support.
Choose Mistral Large 2 when balanced team usage with eu data residency requirements.
Both models serve different primary workflows — consider using each where it has a clear edge.
