Side-by-side comparison of pricing, 12 benchmarks, and generation speed.
| Metric | Mistral Large 3 | Command-R (Mar '24) |
|---|---|---|
| Input ($/M tokens) | $0.5 | $0.5 |
| Output ($/M tokens) | $1.5 | $1.5 |
Verdict. Mistral Large 3 wins the overall benchmark matchup 2–0 across 2 overlapping categories, but raw benchmark score is only one input to the decision.
Pricing. Both models sit in the budget bracket for output-token pricing. At 1.0× the per-million-token cost, Command-R (Mar '24) is meaningfully cheaper if your traffic is output-heavy (long completions, document generation, agent loops). Command-R (Mar '24) makes more sense when output volume is low and absolute reasoning quality justifies the premium.
Strengths. Mistral Large 3 is strongest on Coding Index (20.1), Intelligence Index (15.9). Command-R (Mar '24) leads on Intelligence Index (1.7).
Speed. Speed data is incomplete for this pair; benchmark and price should decide.
Provider. Mistral and Cohere sell to overlapping but distinct developer audiences: Mistral tends to ship frontier reasoning models with premium positioning, while Cohere often prices more aggressively. Your existing vendor relationships, billing, and SLA preferences may matter as much as the raw numbers above.
Workload cost. Workload scenarios (per million requests at 30M input + 15M output tokens): Mistral Large 3 costs $37.50 ($450/year); Command-R (Mar '24) costs $37.50 ($450/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): Mistral Large 3 ≈ $5.50/run, Command-R (Mar '24) ≈ $5.50/run. At agent/realtime scale (200M input / 100M output per million requests): Mistral Large 3 ≈ $250/run, Command-R (Mar '24) ≈ $250/run.
Recommendation. Both models have legitimate use cases — the right answer depends on whether you are optimizing for benchmark ceiling, latency, or unit cost. Start with the cheaper / faster model, evaluate against your specific task, and only switch if the upgrade shows a meaningful lift.
Data from Artificial Analysis API — 12 benchmarks
Both models have similar pricing. Check the detailed breakdown above for input vs output token costs.
Mistral Large 3 wins 2 out of 12 benchmarks compared to 0 for Command-R (Mar '24). See the detailed benchmark chart above for per-category results.
Mistral Large 3 generates tokens faster at 48 tok/s vs — tok/s. Mistral Large 3 also has lower time-to-first-token (1.17s vs —s).
Choose based on your priorities: both are similarly priced, Mistral Large 3 for stronger benchmark performance, and Mistral Large 3 for faster generation. For latency-sensitive apps, check the TTFT comparison above.