Model comparison
Gemma 4 12B vs Ornith-1.0-397B
Head-to-head evidence from 0 shared benchmark results across 0 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Gemma 4 12B #135 (Estimated); Ornith-1.0-397B unranked (Not scored). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Gemma 4 12B and Ornith-1.0-397B share 0 comparable benchmark results. 0 of 8 categories are comparable. 25 results are unique to Gemma 4 12B; 7 to Ornith-1.0-397B.
Updated July 17, 2026- Shared results
- 0
- Gemma 4 12B only
- 25
- Ornith-1.0-397B only
- 7
- Comparable categories
- 0 / 8
Benchmark data for Gemma 4 12B and Ornith-1.0-397B is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 0 shared benchmark results across 0 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.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Gemma 4 12B | Ornith-1.0-397B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Gemma 4 12BNot available | Ornith-1.0-397B$0 input / $0 output | A complete price comparison is not available. |
| Generation speedtokens per second | Gemma 4 12BNot available | Ornith-1.0-397BNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Gemma 4 12BNot available | Ornith-1.0-397BNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Gemma 4 12B256K | Ornith-1.0-397B256K | Listed context windows are equal. |
Benchmark Deep Dive
Agentic3 benchmarks
Coding8 benchmarks
| Benchmark | Gemma 4 12B | Ornith-1.0-397B | Result |
|---|---|---|---|
| LiveCodeBench v6Source | 72.0% | — | Not comparable |
| Terminal-Bench HardSource | 18.2% | — | Not comparable |
| AA-SciCodeSource | 38.2% | — | Not comparable |
| SWE-bench VerifiedSource | — | 82.4% | Not comparable |
| SWE-bench ProSource | — | 62.2% | Not comparable |
| SWE MultilingualSource | — | 78.9% | Not comparable |
| NL2RepoSource | — | 48.2% | Not comparable |
| Terminal-Bench 2.0Source | — | 77.5% | Not comparable |
Reasoning4 benchmarks
Knowledge11 benchmarks
| Benchmark | Gemma 4 12B | Ornith-1.0-397B | 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% | — | Not comparable |
| AA-GPQA DiamondSource | 75.3% | — | Not comparable |
| AA-HLESource | 14.8% | — | Not comparable |
| AA-Omniscience IndexSource | -51.9% | — | Not comparable |
| AA-Omniscience AccuracySource | 16.0% | — | Not comparable |
| AA-Omniscience Hallucination RateSource | 80.8% | — | Not comparable |
Math1 benchmarks
| Benchmark | Gemma 4 12B | Ornith-1.0-397B | Result |
|---|---|---|---|
| AIME26Source | 77.5% | — | Not comparable |
Multimodal4 benchmarks
Inst. Following1 benchmarks
| Benchmark | Gemma 4 12B | Ornith-1.0-397B | Result |
|---|---|---|---|
| AA-IFBenchSource | 73.5% | — | Not comparable |
Frequently Asked Questions (3)
Can I compare Gemma 4 12B and Ornith-1.0-397B 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 Gemma 4 12B and Ornith-1.0-397B today?
Ornith-1.0-397B: $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.
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