Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Granite-4.0-350M
~27
0/8 categoriesMiniMax M2.5
Coming soon
Winner · 0/8 categoriesGranite-4.0-350M· MiniMax M2.5
Benchmark data for Granite-4.0-350M and MiniMax M2.5 is coming soon on BenchLM.
BenchLM does not have sourced benchmark coverage for MiniMax M2.5 yet. This comparison is currently limited to metadata such as context window, reasoning mode, and pricing where available.
MiniMax M2.5 is priced at $0.30 input / $1.20 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Granite-4.0-350M. MiniMax M2.5 has the larger context window at 128K, compared with 32K for Granite-4.0-350M.
BenchLM keeps the benchmark table and the operator tradeoffs on the same page so a better score does not hide a materially slower, pricier, or smaller-context model.
Runtime metrics show N/A when BenchLM does not have a sourced snapshot for that exact model. The scoring rules and freshness policy are documented on the methodology page.
| Benchmark | Granite-4.0-350M | MiniMax M2.5 |
|---|---|---|
| Agentic | ||
| Coming soon | ||
| Coding | ||
| HumanEval | 38% | — |
| Multimodal & Grounded | ||
| Coming soon | ||
| Reasoning | ||
| BBH | 33.3% | — |
| Knowledge | ||
| MMLU | 36.2% | — |
| GPQA | 26.1% | — |
| MMLU-Pro | 14.4% | — |
| Instruction Following | ||
| IFEval | 61.6% | — |
| Multilingual | ||
| MGSM | 16.2% | — |
| Mathematics | ||
| Coming soon | ||
Not fully yet. BenchLM is tracking both models, but the sourced benchmark breakdown for this comparison is still coming soon.
BenchLM only shows category winners and benchmark-level calls when we have sourced results that can be compared fairly. For these models, the public benchmark coverage is not complete enough yet.
Granite-4.0-350M: $0.00 input / $0.00 output per 1M tokens MiniMax M2.5: $0.30 input / $1.20 output per 1M tokens Both model pages still include creator, context window, reasoning mode, and other metadata while benchmark coverage fills in.
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