Model comparison
MiniMax M2.7 vs Soofi S 30B-A3B
Head-to-head evidence from 1 shared benchmark result across 1 category. Overall scores shown here use BenchLM's provisional ranking lane.
Evidence parity. MiniMax M2.7 and Soofi S 30B-A3B share 1 comparable benchmark result. 0 of 8 categories are comparable. 36 results are unique to MiniMax M2.7; 7 to Soofi S 30B-A3B.
Updated July 15, 2026- Shared results
- 1
- MiniMax M2.7 only
- 36
- Soofi S 30B-A3B only
- 7
- Comparable categories
- 0 / 8
Benchmark data for MiniMax M2.7 and Soofi S 30B-A3B is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 1 shared benchmark result across 1 evidence category; 0 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
BenchLM has partial data for these models, but not enough overlapping benchmark coverage to produce a fair score-level comparison yet.
MiniMax M2.7 is priced at $0.30 input / $1.20 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Soofi S 30B-A3B. Soofi S 30B-A3B has the larger context window at 1M, compared with 200K for MiniMax M2.7.
Category breakdown
Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.
| Category | MiniMax M2.7 | Δ | Soofi S 30B-A3B |
|---|---|---|---|
| Agentic | MiniMax M2.757.0 | MarginNo overlap | Soofi S 30B-A3BNot measured |
| Coding | MiniMax M2.754.4 | MarginNo overlap | Soofi S 30B-A3BNot measured |
| Knowledge | MiniMax M2.7Not measured | MarginNo overlap | Soofi S 30B-A3B49.9 |
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | MiniMax M2.7 | Soofi S 30B-A3B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | MiniMax M2.7$0.3 input / $1.2 output | Soofi S 30B-A3B$0 input / $0 output | Soofi S 30B-A3B has the lower combined listed price. |
| Generation speedtokens per second | MiniMax M2.745 tok/s | Soofi S 30B-A3BNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | MiniMax M2.72.53 s | Soofi S 30B-A3BNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | MiniMax M2.7200K | Soofi S 30B-A3B1M | Soofi S 30B-A3B lists the larger context window. |
Benchmark Deep Dive
Agentic11 benchmarks
| Benchmark | MiniMax M2.7 | Soofi S 30B-A3B | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 57% | — | Not comparable |
| τ²-bench resultsSource | 84.8% | — | Not comparable |
| ToolathlonSource | 46.3% | — | Not comparable |
| MLE-Bench LiteSource | 66.6% | — | Not comparable |
| MM-ClawBenchSource | 62.7% | — | Not comparable |
| Claw-EvalSource | 48.7% | — | Not comparable |
| AA Agentic IndexSource | 25.6% | — | Not comparable |
| APEX-Agents-AASource | 10.6% | — | Not comparable |
| GDPval-AASource | 32.9% | — | Not comparable |
| GDPval-AASource | 1158 | — | Not comparable |
| Gert LabsSource | 40.40% | — | Not comparable |
Coding13 benchmarks
| Benchmark | MiniMax M2.7 | Soofi S 30B-A3B | Result |
|---|---|---|---|
| SWE-bench Verified*Source | 75.4% | — | Not comparable |
| SWE-bench ProSource | 56.2% | — | Not comparable |
| SWE-RebenchSource | 51.9% | — | Not comparable |
| SWE MultilingualSource | 76.5% | — | Not comparable |
| Multi-SWE BenchSource | 52.7% | — | Not comparable |
| VIBE-ProSource | 55.6% | — | Not comparable |
| NL2RepoSource | 39.8% | — | Not comparable |
| Vibe Code BenchSource | 27.04% | — | Not comparable |
| React Native EvalsSource | 71.4% | — | Not comparable |
| AA Coding IndexSource | 52.6% | — | Not comparable |
| Terminal-Bench HardSource | 39.4% | — | Not comparable |
| AA-SciCodeSource | 47.0% | — | Not comparable |
| HumanEvalSource | — | 73.8% | Not comparable |
Reasoning4 benchmarks
Knowledge11 benchmarks
| Benchmark | MiniMax M2.7 | Soofi S 30B-A3B | Result |
|---|---|---|---|
| GPQA-DSource | 87.0% | 43.4% | MiniMax M2.7 leads |
| MMLU-Pro (Arcee)Source | 80.8% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 38.1% | — | Not comparable |
| AA-GPQA DiamondSource | 87.4% | — | Not comparable |
| AA-HLESource | 28.1% | — | Not comparable |
| AA-Omniscience IndexSource | 0.7% | — | Not comparable |
| AA-Omniscience AccuracySource | 26.1% | — | Not comparable |
| AA-Omniscience Hallucination RateSource | 34.4% | — | Not comparable |
| GPQASource | — | 43.4% | Not comparable |
| MMLU-ProSource | — | 51.4% | Not comparable |
| AGIEvalSource | — | 66.9% | Not comparable |
Math2 benchmarks
Multimodal2 benchmarks
Inst. Following1 benchmarks
| Benchmark | MiniMax M2.7 | Soofi S 30B-A3B | Result |
|---|---|---|---|
| AA-IFBenchSource | 75.7% | — | Not comparable |
Frequently Asked Questions (3)
Can I compare MiniMax M2.7 and Soofi S 30B-A3B on BenchLM yet?
Not fully yet. BenchLM is tracking both models, but the sourced benchmark breakdown for this comparison is still coming soon.
Why does this comparison show “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.
What data is available for MiniMax M2.7 and Soofi S 30B-A3B today?
MiniMax M2.7: $0.30 input / $1.20 output per 1M tokens Soofi S 30B-A3B: $0.00 input / $0.00 output per 1M tokens Both model pages still include creator, context window, reasoning mode, and other metadata while benchmark coverage fills in.
Related Comparisons
Explore More
The AI models change fast. We track them for you.
A weekly brief for engineers and researchers covering new models, ranking shifts, and pricing changes.
Free. No spam. Unsubscribe anytime.