Model comparison
Celeris-1 vs Qwen3.5 397B
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); Qwen3.5 397B #71 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Celeris-1 and Qwen3.5 397B share 1 comparable benchmark result. 1 of 8 categories are comparable. 0 results are unique to Celeris-1; 54 to Qwen3.5 397B.
Updated July 24, 2026- Shared results
- 1
- Celeris-1 only
- 0
- Qwen3.5 397B only
- 54
- Comparable categories
- 1 / 8
Treat this as a split decision. Celeris-1 makes more sense if knowledge is the priority; Qwen3.5 397B is the better fit if you want the cheaper token bill or you need the larger 128K 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 Qwen3.5 397B 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.
Celeris-1 is also the more expensive model on tokens at $2.00 input / $6.00 output per 1M tokens, versus $0.60 input / $3.60 output per 1M tokens for Qwen3.5 397B. Qwen3.5 397B gives you the larger context window at 128K, 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 | Qwen3.5 397B |
|---|---|---|---|
| Knowledge | Celeris-175.9 | Margin← 19.3 | Qwen3.5 397B56.6 |
| Agentic | Celeris-1Not measured | MarginNo overlap | Qwen3.5 397B56.5 |
| Coding | Celeris-1Not measured | MarginNo overlap | Qwen3.5 397B66.5 |
| Reasoning | Celeris-1Not measured | MarginNo overlap | Qwen3.5 397B63.2 |
| Math | Celeris-1Not measured | MarginNo overlap | Qwen3.5 397B90.6 |
| Multilingual | Celeris-1Not measured | MarginNo overlap | Qwen3.5 397B84.7 |
| Multimodal | Celeris-1Not measured | MarginNo overlap | Qwen3.5 397B79.6 |
| Inst. Following | Celeris-1Not measured | MarginNo overlap | Qwen3.5 397B92.6 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
MMLU-Pro
KnowledgeA 75.9%B 87.8%Winner: Qwen3.5 397BΔ 11.9MMLU-Pro: Celeris-1 scored 75.9%; Qwen3.5 397B scored 87.8%. Qwen3.5 397B wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Celeris-1 | Qwen3.5 397B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Celeris-1$2 input / $6 output | Qwen3.5 397B$0.6 input / $3.6 output | Qwen3.5 397B has the lower combined listed price. |
| Generation speedtokens per second | Celeris-1Not available | Qwen3.5 397B96 tok/s | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Celeris-1Not available | Qwen3.5 397B2.44 s | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Celeris-18K | Qwen3.5 397B128K | Qwen3.5 397B lists the larger context window. |
Benchmark Deep Dive
Agentic18 benchmarks
| Benchmark | Celeris-1 | Qwen3.5 397B | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | — | 52.5% | Not comparable |
| BrowseCompSource | — | 62% | Not comparable |
| Claw-EvalSource | — | 56.8% | Not comparable |
| QwenClawBenchSource | — | 51.8% | Not comparable |
| τ³-bench resultsSource | — | 68.4% | Not comparable |
| VITA-BenchSource | — | 43.7% | Not comparable |
| DeepPlanningSource | — | 37.6% | Not comparable |
| ToolathlonSource | — | 36.3% | Not comparable |
| MCP AtlasSource | — | 46.1% | Not comparable |
| MCP-TasksSource | — | 74.2% | Not comparable |
| WideResearchSource | — | 74.0% | Not comparable |
| τ²-bench resultsSource | — | 95.6% | Not comparable |
| Gert LabsSource | — | 46.76% | Not comparable |
| ResearchClawBenchSource | — | 14.2% | Not comparable |
| AA Agentic IndexSource | — | 19.9% | Not comparable |
| APEX-Agents-AASource | — | 15.3% | Not comparable |
| GDPval-AASource | — | 23.1% | Not comparable |
| GDPval-AASource | — | 962 | Not comparable |
Coding5 benchmarks
Reasoning4 benchmarks
KnowledgeCeleris-1 wins12 benchmarks
| Benchmark | Celeris-1 | Qwen3.5 397B | Result |
|---|---|---|---|
| MMLU-ProSource | 75.9% | 87.8% | Qwen3.5 397B leads |
| GPQASource | — | 88.4% | Not comparable |
| SuperGPQASource | — | 70.4% | Not comparable |
| MMLU-ReduxSource | — | 94.9% | Not comparable |
| C-EvalSource | — | 93% | Not comparable |
| HLESource | — | 28.7% | Not comparable |
| Artificial Analysis Intelligence IndexSource | — | 33.7% | Not comparable |
| AA-GPQA DiamondSource | — | 89.3% | Not comparable |
| AA-HLESource | — | 27.3% | Not comparable |
| AA-Omniscience IndexSource | — | -29.8% | Not comparable |
| AA-Omniscience AccuracySource | — | 31.4% | Not comparable |
| AA-Omniscience Hallucination RateSource | — | 89.1% | Not comparable |
Math5 benchmarks
Multilingual2 benchmarks
Multimodal7 benchmarks
Frequently Asked Questions (2)
Which is better, Celeris-1 or Qwen3.5 397B?
Celeris-1 and Qwen3.5 397B 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 Qwen3.5 397B?
Celeris-1 has the edge for knowledge tasks in this comparison, averaging 75.9 versus 56.6. Inside this category, MMLU-Pro is the benchmark that creates the most daylight between them.
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