DeepSeek V3 wins on coding (87 vs 72) and price ($0.27 vs $3/1M input). For most workflows, DeepSeek V3 is the stronger default — gpt-4o-class coding quality at under $0.30/1m — the best value in the directory.
The shortest way to see the safest default, the lower-cost option, and the specialist pick before you read deeper.
DeepSeek V3 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.
DeepSeek / Budget / Mar 24, 2026
GPT-4o-class coding quality at under $0.30/1M — the best value in the directory.
Ranks models by the broadest mix of coding, writing, research, and long-context usefulness.
Your team has data sovereignty requirements or needs enterprise-grade reliability guarantees.
The fastest way to see where the recommendation shifts when your priority changes.
GPT-4o class coding and reasoning at under $0.30/1M input tokens
Open-source weights available for self-hosting
Strong performance on HumanEval and coding benchmarks relative to price
Chinese-origin model raises data sovereignty concerns for some enterprise teams
Slightly weaker on nuanced English writing tone compared to Claude and GPT
UseRightAI recommendations are based on practical decision factors people actually feel in day-to-day use.
Newsletter
Useful if you care about ranking shifts, pricing changes, or a better recommendation appearing in this decision path.
No spam. Useful updates only. Affiliate disclosures always clearly labeled.
DeepSeek V3 wins on more categories — coding, research, 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.
DeepSeek V3 is cheaper at $0.27/1M input and $1.1/1M output. Mistral Large 2 costs $3/1M input and $9/1M output.
Both DeepSeek V3 and Mistral Large 2 have the same 128K context window.
DeepSeek V3 is better for coding with a score of 87 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.
DeepSeek V3 is faster with a fast speed rating (score: 4) 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.
DeepSeek V3 leads on coding with a score of 87 vs 72 for Mistral Large 2.
DeepSeek V3 is cheaper at $0.27/1M input tokens vs $3/1M for Mistral Large 2.
DeepSeek V3 is the stronger default for coding tasks.
Choose DeepSeek V3 for coding and research — coding.
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.
Less reliable for complex multi-step agentic workflows vs frontier models
