Model comparison
Celeris-1 vs Qwen3 235B 2507
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 235B 2507 #78 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Celeris-1 and Qwen3 235B 2507 share 1 comparable benchmark result. 1 of 8 categories are comparable. 0 results are unique to Celeris-1; 3 to Qwen3 235B 2507.
Updated July 24, 2026- Shared results
- 1
- Celeris-1 only
- 0
- Qwen3 235B 2507 only
- 3
- Comparable categories
- 1 / 8
Treat this as a split decision. Celeris-1 makes more sense if its workflow fits your team better; Qwen3 235B 2507 is the better fit if knowledge is the priority or you want the cheaper token bill.
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 235B 2507 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 $0.00 input / $0.00 output per 1M tokens for Qwen3 235B 2507. That is roughly Infinityx on output cost alone. Qwen3 235B 2507 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 235B 2507 |
|---|---|---|---|
| Knowledge | Celeris-175.9 | Margin→ 3.0 | Qwen3 235B 250778.9 |
| Multilingual | Celeris-1Not measured | MarginNo overlap | Qwen3 235B 250779.4 |
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 83%Winner: Qwen3 235B 2507Δ 7.1MMLU-Pro: Celeris-1 scored 75.9%; Qwen3 235B 2507 scored 83%. Qwen3 235B 2507 wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Celeris-1 | Qwen3 235B 2507 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Celeris-1$2 input / $6 output | Qwen3 235B 2507$0 input / $0 output | Qwen3 235B 2507 has the lower combined listed price. |
| Generation speedtokens per second | Celeris-1Not available | Qwen3 235B 2507Not available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Celeris-1Not available | Qwen3 235B 2507Not available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Celeris-18K | Qwen3 235B 2507128K | Qwen3 235B 2507 lists the larger context window. |
Benchmark Deep Dive
Frequently Asked Questions (2)
Which is better, Celeris-1 or Qwen3 235B 2507?
Celeris-1 and Qwen3 235B 2507 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 235B 2507?
Qwen3 235B 2507 has the edge for knowledge tasks in this comparison, averaging 78.9 versus 75.9. Inside this category, MMLU-Pro is the benchmark that creates the most daylight between them.
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