MiniMax M2.1 vs Pixtral Large: Specs & Benchmark Comparison
| Characteristic | MiniMax M2.1 | Pixtral Large |
|---|---|---|
| Company | MiniMax | Mistral AI |
| Release Date | December 22, 2025 | November 18, 2024 |
| Parameters | — | 124B |
| Multimodal | No | Yes |
| Context (input) | 1.0M | 128K |
| Context (output) | 100K | 128K |
| Input Price / 1M | $0.30 | $2.00 |
| Output Price / 1M | $1.20 | $6.00 |
| Average Score | 0.9 | 0.8 |
Verdict
MiniMax M2.1 leads in 3 out of 4 comparison categories.
Overall Performance
Both models show comparable average scores: MiniMax M2.1 — 0.9, Pixtral Large — 0.8.
API Cost
MiniMax M2.1 is 5.3x cheaper: input $0.30/1M vs $2.00/1M tokens.
Context Window
MiniMax M2.1 supports a larger context: 1M vs 128K tokens.
Recency
MiniMax M2.1 is newer: released 12/22/2025 vs 11/18/2024.
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Frequently Asked Questions
Which is better for coding — MiniMax M2.1 or Pixtral Large?
Direct comparison on the SWE-Bench benchmark is not available. We recommend reviewing other metrics on the comparison page.
Which model is cheaper — MiniMax M2.1 or Pixtral Large?
MiniMax M2.1 is cheaper for input: $0.30 per 1M tokens vs $2.00.
Which has a larger context window — MiniMax M2.1 or Pixtral Large?
MiniMax M2.1 supports a larger context: 1,000,000 tokens vs 128,000.
The MiniMax M2.1 and Pixtral Large comparison is updated for 2026. Data includes benchmark results, API pricing, context window size and other specifications. For more detailed information, visit the MiniMax M2.1 or Pixtral Large page. See also the complete list of AI model comparisons.