Celeris-1 vs Qwen3.8-Flash-Next
Which is better for the money: Celeris-1 by Celeris or Qwen3.8-Flash-Next by Alibaba? Intelligence, total benchmark cost, and end-to-end time from Artificial Analysis & other sources, snapshot 2026-10-25.
Trade-off
Verdict
Depends on your budget
Qwen3.8-Flash-Next scores 33.5 points higher (39.8 vs 6.3) but costs 6.0× as much to run the benchmark ($363 vs $60.0; both mid-range class). They are not alternatives at one budget: pick Qwen3.8-Flash-Next when you need intelligence above 6.3, and Celeris-1 when 6.3 is enough.
| Metric | Celeris-1 | Qwen3.8-Flash-Next | Difference |
|---|---|---|---|
| Intelligence (higher is better) | 6.3 | 39.8 | +531.7% Qwen3.8-Flash-Next is 6.3× more intelligent |
| Total AA cost (lower is better) | $59.99 | $362.72 | +504.6% Qwen3.8-Flash-Next is 6.0× more expensive |
| End-to-end time (lower is better) | 0.87s | 50.25s | +5675.9% Qwen3.8-Flash-Next is 5675.9% slower |
| Price per 1M tokens (in / out) | $0.20 / $0.70 | $0.15 / $0.47 | |
| Input modalities | Text, Image | Text, Image, Video |
Qwen3.8-Flash-Next vs Celeris-1: 531.7% more intelligence, 504.6% more cost to run the AA benchmark, and 5675.9% slower end-to-end.
Today's Pareto frontier
Against the frontier
- Celeris-1 is off the frontier: at the same or lower cost, Claude Haiku 5.5 (Medium) scores 34.50 for $56.4.
- Qwen3.8-Flash-Next is off the frontier: at the same or lower cost, GPT-6.1 Sol (Medium) scores 47.80 for $361.
Celeris-1Qwen3.8-Flash-NextToday's Pareto frontierOpen-weights frontierEvery other model
Matchup
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Accept: text/markdown or ?format=md returns this page as Markdown. JSON: /api/v1/compare/celeris-1/qwen3-8-flash-next · Markdown: /api/v1/compare/celeris-1/qwen3-8-flash-next?format=md · llms.txt · agent skill