Model comparison
Celeris-1 vs Claude Sonnet 4.6
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); Claude Sonnet 4.6 #32 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Celeris-1 and Claude Sonnet 4.6 share 1 comparable benchmark result. 1 of 8 categories are comparable. 0 results are unique to Celeris-1; 32 to Claude Sonnet 4.6.
Updated July 24, 2026- Shared results
- 1
- Celeris-1 only
- 0
- Claude Sonnet 4.6 only
- 32
- Comparable categories
- 1 / 8
Treat this as a split decision. Celeris-1 makes more sense if knowledge is the priority or you want the cheaper token bill; Claude Sonnet 4.6 is the better fit if you need the larger 200K 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 Claude Sonnet 4.6 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.
Claude Sonnet 4.6 is also the more expensive model on tokens at $3.00 input / $15.00 output per 1M tokens, versus $2.00 input / $6.00 output per 1M tokens for Celeris-1. That is roughly 2.5x on output cost alone. Claude Sonnet 4.6 gives you the larger context window at 200K, 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 | Claude Sonnet 4.6 |
|---|---|---|---|
| Knowledge | Celeris-175.9 | Margin← 9.9 | Claude Sonnet 4.666.0 |
| Agentic | Celeris-1Not measured | MarginNo overlap | Claude Sonnet 4.665.2 |
| Coding | Celeris-1Not measured | MarginNo overlap | Claude Sonnet 4.669.1 |
| Math | Celeris-1Not measured | MarginNo overlap | Claude Sonnet 4.626.4 |
| Multimodal | Celeris-1Not measured | MarginNo overlap | Claude Sonnet 4.677.4 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
MMLU-Pro
KnowledgeA 75.9%B 79.2%Winner: Claude Sonnet 4.6Δ 3.3MMLU-Pro: Celeris-1 scored 75.9%; Claude Sonnet 4.6 scored 79.2%. Claude Sonnet 4.6 wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Celeris-1 | Claude Sonnet 4.6 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Celeris-1$2 input / $6 output | Claude Sonnet 4.6$3 input / $15 output | Celeris-1 has the lower combined listed price. |
| Generation speedtokens per second | Celeris-1Not available | Claude Sonnet 4.644 tok/s | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Celeris-1Not available | Claude Sonnet 4.61.48 s | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Celeris-18K | Claude Sonnet 4.6200K | Claude Sonnet 4.6 lists the larger context window. |
Benchmark Deep Dive
Agentic8 benchmarks
| Benchmark | Celeris-1 | Claude Sonnet 4.6 | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | — | 59.1% | Not comparable |
| OSWorld-VerifiedSource | — | 72.1% | Not comparable |
| Claw-EvalSource | — | 67.8% | Not comparable |
| CyberGymSource | — | 65.2% | Not comparable |
| τ²-bench resultsSource | — | 79.5% | Not comparable |
| Gert LabsSource | — | 62.92% | Not comparable |
| OSWorld 2.0Source | — | 8.3% | Not comparable |
| JobBenchSource | — | 36.9% | Not comparable |
Coding7 benchmarks
| Benchmark | Celeris-1 | Claude Sonnet 4.6 | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | — | 79.6% | Not comparable |
| SWE-RebenchSource | — | 60.7% | Not comparable |
| React Native EvalsSource | — | 80.6% | Not comparable |
| Vibe Code BenchSource | — | 51.48% | Not comparable |
| cursorBench31Source | — | 48.8% | Not comparable |
| AA-SciCodeSource | — | 46.9% | Not comparable |
| FrontierCode 1.1 MainSource | — | 24.3% | Not comparable |
Reasoning2 benchmarks
KnowledgeCeleris-1 wins10 benchmarks
| Benchmark | Celeris-1 | Claude Sonnet 4.6 | Result |
|---|---|---|---|
| MMLU-ProSource | 75.9% | 79.2% | Claude Sonnet 4.6 leads |
| GPQASource | — | 89.9% | Not comparable |
| SuperGPQASource | — | 95% | Not comparable |
| HLESource | — | 49% | Not comparable |
| Artificial Analysis Intelligence IndexSource | — | 35.9% | Not comparable |
| AA-GPQA DiamondSource | — | 79.9% | Not comparable |
| AA-HLESource | — | 13.2% | Not comparable |
| AA-Omniscience IndexSource | — | -2.9% | Not comparable |
| AA-Omniscience AccuracySource | — | 38.0% | Not comparable |
| AA-Omniscience Hallucination RateSource | — | 65.9% | Not comparable |
Math2 benchmarks
Multimodal3 benchmarks
Inst. Following1 benchmarks
| Benchmark | Celeris-1 | Claude Sonnet 4.6 | Result |
|---|---|---|---|
| AA-IFBenchSource | — | 41.2% | Not comparable |
Frequently Asked Questions (2)
Which is better, Celeris-1 or Claude Sonnet 4.6?
Celeris-1 and Claude Sonnet 4.6 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 Claude Sonnet 4.6?
Celeris-1 has the edge for knowledge tasks in this comparison, averaging 75.9 versus 66. Inside this category, MMLU-Pro is the benchmark that creates the most daylight between them.
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