Model comparison
Celeris-1 vs Gemma 4 12B
Head-to-head evidence from 1 shared benchmark result across 1 category. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Celeris-1 unranked (Not scored); Gemma 4 12B #137 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Celeris-1 and Gemma 4 12B share 1 comparable benchmark result. 1 of 8 categories are comparable. 0 results are unique to Celeris-1; 22 to Gemma 4 12B.
Updated July 24, 2026- Shared results
- 1
- Celeris-1 only
- 0
- Gemma 4 12B only
- 22
- Comparable categories
- 1 / 8
Treat this as a split decision. Celeris-1 makes more sense if you would rather avoid the extra latency and token burn of a reasoning model; Gemma 4 12B is the better fit if knowledge is the priority or you need the larger 256K context window.
Confidence note. This is a partial-evidence comparison with 1 shared benchmark result across 1 evidence category; 1 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
Celeris-1 and Gemma 4 12B finish on the same BenchAlign overall score, so this is less about a single winner and more about where the edge shows up. The BenchAlign headline says tie; the benchmark table is where the real choice happens.
Gemma 4 12B is the reasoning model in the pair, while Celeris-1 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. Gemma 4 12B gives you the larger context window at 256K, compared with 8K for Celeris-1.
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 | Celeris-1 | Δ | Gemma 4 12B |
|---|---|---|---|
| Knowledge | Celeris-175.9 | Margin→ 1.6 | Gemma 4 12B77.5 |
| Reasoning | Celeris-1Not measured | MarginNo overlap | Gemma 4 12B43.4 |
| Math | Celeris-1Not measured | MarginNo overlap | Gemma 4 12B77.5 |
| Multimodal | Celeris-1Not measured | MarginNo overlap | Gemma 4 12B69.1 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
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- Source ↗
MMLU-Pro
KnowledgeA 75.9%B 77.2%Winner: Gemma 4 12BΔ 1.3MMLU-Pro: Celeris-1 scored 75.9%; Gemma 4 12B scored 77.2%. Gemma 4 12B wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Celeris-1 | Gemma 4 12B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Celeris-1$2 input / $6 output | Gemma 4 12BNot available | A complete price comparison is not available. |
| Generation speedtokens per second | Celeris-1Not available | Gemma 4 12BNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Celeris-1Not available | Gemma 4 12BNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Celeris-18K | Gemma 4 12B256K | Gemma 4 12B lists the larger context window. |
Benchmark Deep Dive
Agentic1 benchmarks
| Benchmark | Celeris-1 | Gemma 4 12B | Result |
|---|---|---|---|
| τ²-bench resultsSource | — | 36.3% | Not comparable |
Coding1 benchmarks
| Benchmark | Celeris-1 | Gemma 4 12B | Result |
|---|---|---|---|
| AA-SciCodeSource | — | 38.2% | Not comparable |
Reasoning4 benchmarks
KnowledgeGemma 4 12B wins11 benchmarks
| Benchmark | Celeris-1 | Gemma 4 12B | Result |
|---|---|---|---|
| MMLU-ProSource | 75.9% | 77.2% | Gemma 4 12B leads |
| GPQASource | — | 78.8% | Not comparable |
| GPQA-DSource | — | 78.8% | 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 | Celeris-1 | Gemma 4 12B | Result |
|---|---|---|---|
| AIME26Source | — | 77.5% | Not comparable |
Multimodal4 benchmarks
Inst. Following1 benchmarks
| Benchmark | Celeris-1 | Gemma 4 12B | Result |
|---|---|---|---|
| AA-IFBenchSource | — | 73.5% | Not comparable |
Frequently Asked Questions (2)
Which is better, Celeris-1 or Gemma 4 12B?
Celeris-1 and Gemma 4 12B are tied on the BenchAlign overall score, so the right pick depends on which category matters most for your use case.
Which is better for knowledge tasks, Celeris-1 or Gemma 4 12B?
Gemma 4 12B has the edge for knowledge tasks in this comparison, averaging 77.5 versus 75.9. Inside this category, MMLU-Pro is the benchmark that creates the most daylight between them.
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