Granite 4.2 30B vs Qwen3.8-Flash-Next
Which is better for the money: Granite 4.2 30B by IBM or Qwen3.8-Flash-Next by Alibaba? Intelligence, total benchmark cost, and end-to-end time from Artificial Analysis & other sources, snapshot 2026-10-26.
Trade-off
Verdict
Depends on your budget
Qwen3.8-Flash-Next scores 27.1 points higher (39.8 vs 12.7) but costs 3.3× as much to run the benchmark ($363 vs $111; both mid-range class). They are not alternatives at one budget: pick Qwen3.8-Flash-Next when you need intelligence above 12.7, and Granite 4.2 30B when 12.7 is enough.
| Metric | Granite 4.2 30B | Qwen3.8-Flash-Next | Difference |
|---|---|---|---|
| Intelligence (higher is better) | 12.7 | 39.8 | +213.4% Qwen3.8-Flash-Next is 3.1× more intelligent |
| Total AA cost (lower is better) | $110.83 | $362.72 | +227.3% Qwen3.8-Flash-Next is 3.3× more expensive |
| End-to-end time (lower is better) | 57.71s | 50.51s | −12.5% Qwen3.8-Flash-Next is 12.5% faster |
| Price per 1M tokens (in / out) | $0.16 / $0.65 | $0.15 / $0.47 | |
| Input modalities | Text | Text, Image, Video |
Qwen3.8-Flash-Next vs Granite 4.2 30B: 213.4% more intelligence, 227.3% more cost to run the AA benchmark, and 12.5% faster end-to-end.
Today's Pareto frontier
Against the frontier
- Granite 4.2 30B is off the frontier: at the same or lower cost, MiMo-V2.6-Flash scores 37.90 for $110.
- Qwen3.8-Flash-Next is off the frontier: at the same or lower cost, GPT-6.1 Sol (Medium) scores 47.80 for $361.
Granite 4.2 30BQwen3.8-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/granite-4-2-30b/qwen3-8-flash-next · Markdown: /api/v1/compare/granite-4-2-30b/qwen3-8-flash-next?format=md · llms.txt · agent skill