Model comparison
Gemma 4 12B vs MiMo-V2-Omni
Head-to-head evidence from 12 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Gemma 4 12B #137 (Estimated); MiMo-V2-Omni #40 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Gemma 4 12B and MiMo-V2-Omni share 12 comparable benchmark results. 0 of 8 categories are comparable. 11 results are unique to Gemma 4 12B; 2 to MiMo-V2-Omni.
Updated July 23, 2026- Shared results
- 12
- Gemma 4 12B only
- 11
- MiMo-V2-Omni only
- 2
- Comparable categories
- 0 / 8
Benchmark data for Gemma 4 12B and MiMo-V2-Omni is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 12 shared benchmark results across 6 evidence categories; 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.
MiMo-V2-Omni has the larger context window at 262K, compared with 256K for Gemma 4 12B.
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 12B | Δ | MiMo-V2-Omni |
|---|---|---|---|
| Coding | Gemma 4 12BNot measured | MarginNo overlap | MiMo-V2-Omni74.8 |
| Reasoning | Gemma 4 12B43.4 | MarginNo overlap | MiMo-V2-OmniNot measured |
| Knowledge | Gemma 4 12B77.5 | MarginNo overlap | MiMo-V2-OmniNot measured |
| Math | Gemma 4 12B77.5 | MarginNo overlap | MiMo-V2-OmniNot measured |
| Multimodal | Gemma 4 12B69.1 | MarginNo overlap | MiMo-V2-OmniNot measured |
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Gemma 4 12B | MiMo-V2-Omni | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Gemma 4 12BNot available | MiMo-V2-OmniNot available | A complete price comparison is not available. |
| Generation speedtokens per second | Gemma 4 12BNot available | MiMo-V2-OmniNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Gemma 4 12BNot available | MiMo-V2-OmniNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Gemma 4 12B256K | MiMo-V2-Omni262K | MiMo-V2-Omni lists the larger context window. |
Benchmark Deep Dive
Agentic2 benchmarks
Coding2 benchmarks
Reasoning4 benchmarks
Knowledge11 benchmarks
| Benchmark | Gemma 4 12B | MiMo-V2-Omni | Result |
|---|---|---|---|
| GPQASource | 78.8% | — | Not comparable |
| GPQA-DSource | 78.8% | — | Not comparable |
| MMLU-ProSource | 77.2% | — | Not comparable |
| HLE w/o toolsSource | 5.2% | — | Not comparable |
| MMMLUSource | 83.4% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 22.0% | 35.0% | MiMo-V2-Omni leads |
| AA-GPQA DiamondSource | 75.3% | 82.8% | MiMo-V2-Omni leads |
| AA-HLESource | 14.8% | 19.9% | MiMo-V2-Omni leads |
| AA-Omniscience IndexSource | -51.9% | -17.4% | MiMo-V2-Omni leads |
| AA-Omniscience AccuracySource | 16.0% | 18.7% | MiMo-V2-Omni leads |
| AA-Omniscience Hallucination RateSource | 80.8% | 44.4% | MiMo-V2-Omni leads |
Math1 benchmarks
| Benchmark | Gemma 4 12B | MiMo-V2-Omni | Result |
|---|---|---|---|
| AIME26Source | 77.5% | — | Not comparable |
Multimodal4 benchmarks
Inst. Following1 benchmarks
| Benchmark | Gemma 4 12B | MiMo-V2-Omni | Result |
|---|---|---|---|
| AA-IFBenchSource | 73.5% | 53.5% | Gemma 4 12B leads |
Frequently Asked Questions (2)
Can I compare Gemma 4 12B and MiMo-V2-Omni 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.
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