Model comparison
Gemma 4 26B A4B vs MiniMax M3
Head-to-head evidence from 18 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Verified leaderboard positions: Gemma 4 26B A4B unranked; MiniMax M3 #18
BenchAlign evidence: Gemma 4 26B A4B supported; MiniMax M3 supported. Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Gemma 4 26B A4B and MiniMax M3 share 18 comparable benchmark results. 1 of 8 categories are comparable. 3 results are unique to Gemma 4 26B A4B; 27 to MiniMax M3.
Updated July 16, 2026- Shared results
- 18
- Gemma 4 26B A4B only
- 3
- MiniMax M3 only
- 27
- Comparable categories
- 1 / 8
Pick MiniMax M3 if you want the stronger benchmark profile. Gemma 4 26B A4B only becomes the better choice if multimodal & grounded is the priority or you want the cheaper token bill.
Confidence note. This is a partial-evidence comparison with 18 shared benchmark results across 6 evidence categories; 1 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
MiniMax M3 is clearly ahead on the provisional aggregate, 70 to 56. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
MiniMax M3 is also the more expensive model on tokens at $0.30 input / $1.20 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Gemma 4 26B A4B. That is roughly Infinityx on output cost alone. Gemma 4 26B A4B is the reasoning model in the pair, while MiniMax M3 is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. MiniMax M3 gives you the larger context window at 1M, compared with 256K for Gemma 4 26B A4B.
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 | Gemma 4 26B A4B | Δ | MiniMax M3 |
|---|---|---|---|
| Multimodal | Gemma 4 26B A4B73.8 | Margin← 8.9 | MiniMax M364.9 |
| Agentic | Gemma 4 26B A4BNot measured | MarginNo overlap | MiniMax M372.3 |
| Coding | Gemma 4 26B A4BNot measured | MarginNo overlap | MiniMax M372.2 |
| Knowledge | Gemma 4 26B A4B43.8 | MarginNo overlap | MiniMax M3Not measured |
| Math | Gemma 4 26B A4BNot measured | MarginNo overlap | MiniMax M385.7 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
MMMU-Pro
MultimodalA 73.8%B 78.1%Winner: MiniMax M3Δ 4.3MMMU-Pro: Gemma 4 26B A4B scored 73.8%; MiniMax M3 scored 78.1%. MiniMax M3 wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Gemma 4 26B A4B | MiniMax M3 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Gemma 4 26B A4B$0 input / $0 output | MiniMax M3$0.3 input / $1.2 output | Gemma 4 26B A4B has the lower combined listed price. |
| Generation speedtokens per second | Gemma 4 26B A4BNot available | MiniMax M3Not available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Gemma 4 26B A4BNot available | MiniMax M3Not available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Gemma 4 26B A4B256K | MiniMax M31M | MiniMax M3 lists the larger context window. |
Benchmark Deep Dive
Agentic16 benchmarks
| Benchmark | Gemma 4 26B A4B | MiniMax M3 | Result |
|---|---|---|---|
| AA Agentic IndexSource | 11.0% | 35.4% | MiniMax M3 leads |
| τ²-bench resultsSource | 43.6% | 88.9% | MiniMax M3 leads |
| GDPval-AASource | 13.1% | 44.7% | MiniMax M3 leads |
| GDPval-AASource | 761 | 1395 | MiniMax M3 leads |
| Terminal-Bench 2.0Source | — | 66% | Not comparable |
| BrowseCompSource | — | 83.5% | Not comparable |
| OSWorld-VerifiedSource | — | 70.1% | Not comparable |
| MCP AtlasSource | — | 74.2% | Not comparable |
| Claw-EvalSource | — | 74.5% | Not comparable |
| GDPval rubricsSource | — | 74.7% | Not comparable |
| BankerToolBenchSource | — | 76.1% | Not comparable |
| ResearchClawBenchSource | — | 19.8% | Not comparable |
| OSWorld 2.0Source | — | 4.6% | Not comparable |
| AA BriefcaseSource | — | 1110 | Not comparable |
| AA EnterpriseOps-GymSource | — | 32.1% | Not comparable |
| AA Harvey LABSource | — | 6.7% | Not comparable |
Coding11 benchmarks
| Benchmark | Gemma 4 26B A4B | MiniMax M3 | Result |
|---|---|---|---|
| AA Coding IndexSource | 39.3% | 58.6% | MiniMax M3 leads |
| Terminal-Bench HardSource | 13.6% | 42.4% | MiniMax M3 leads |
| AA-SciCodeSource | 40.0% | 45.4% | MiniMax M3 leads |
| SWE-bench VerifiedSource | — | 80.5% | Not comparable |
| SWE-bench ProSource | — | 59% | Not comparable |
| Terminal-Bench 2.0Source | — | 66.0% | Not comparable |
| NL2RepoSource | — | 42.1% | Not comparable |
| VIBE V2Source | — | 50.1% | Not comparable |
| SVG-BenchSource | — | 63.7% | Not comparable |
| KernelBench HardSource | — | 28.8% | Not comparable |
| AA Terminal-Bench 2.1Source | — | 65.2% | Not comparable |
Reasoning2 benchmarks
Knowledge10 benchmarks
| Benchmark | Gemma 4 26B A4B | MiniMax M3 | Result |
|---|---|---|---|
| MMLU-ProSource | 82.6% | — | Not comparable |
| HLESource | 17.2% | — | Not comparable |
| HLE w/o toolsSource | 8.7% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 25.7% | 44.4% | MiniMax M3 leads |
| AA-GPQA DiamondSource | 79.2% | 92.9% | MiniMax M3 leads |
| AA-HLESource | 18.3% | 37.1% | MiniMax M3 leads |
| AA-Omniscience IndexSource | -48.1% | 1.4% | MiniMax M3 leads |
| AA-Omniscience AccuracySource | 18.2% | 15.0% | Gemma 4 26B A4B leads |
| AA-Omniscience Hallucination RateSource | 80.9% | 16.1% | MiniMax M3 leads |
| AA Openness IndexSource | — | 33.3% | Not comparable |
Math1 benchmarks
| Benchmark | Gemma 4 26B A4B | MiniMax M3 | Result |
|---|---|---|---|
| USAMO 2026Source | — | 85.7% | Not comparable |
MultimodalGemma 4 26B A4B wins7 benchmarks
| Benchmark | Gemma 4 26B A4B | MiniMax M3 | Result |
|---|---|---|---|
| MMMU-ProSource | 73.8% | 78.1% | MiniMax M3 leads |
| AA-MMMU-ProSource | 69.2% | 78.6% | MiniMax M3 leads |
| OfficeQA ProSource | — | 45.1% | Not comparable |
| OmniDocBench 1.5Source | — | 91.6% | Not comparable |
| VideoMMMUSource | — | 84.6% | Not comparable |
| Video-MME (with subtitle)Source | — | 85.4% | Not comparable |
| Design Arena WebsiteSource | — | 1294 | Not comparable |
Inst. Following1 benchmarks
| Benchmark | Gemma 4 26B A4B | MiniMax M3 | Result |
|---|---|---|---|
| AA-IFBenchSource | 72.4% | 82.9% | MiniMax M3 leads |
Frequently Asked Questions (2)
Which is better, Gemma 4 26B A4B or MiniMax M3?
MiniMax M3 is ahead on BenchLM's provisional leaderboard, 70 to 56. The biggest single separator in this matchup is MMMU-Pro, where the scores are 73.8% and 78.1%.
Which is better for multimodal and grounded tasks, Gemma 4 26B A4B or MiniMax M3?
Gemma 4 26B A4B has the edge for multimodal and grounded tasks in this comparison, averaging 73.8 versus 64.9. Inside this category, AA-MMMU-Pro is the benchmark that creates the most daylight between them.
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.