qwen3-coder-next: benchmark scores, price and ranking
qwen3-coder-next from Alibaba ranks #575 of 743 LLMs on the LLMs Tiger aggregate benchmark score (45.5), based on 3 benchmark results captured up to 2026-10-13.
- Organisation
- Alibaba
- Type
- Open-weight / local model
- Open weights
- Yes
- Released
- 2026-02-02 (source: epoch)
- Cheapest API price
- $0.120 in / $0.800 out per million tokens (via openrouter, observed 2026-10-13T20:47Z)
- Aggregate rank
- #575 of 743 (score 45.5)
Relative to other models, qwen3-coder-next is strongest on WeirdML (#83 of 109) and weakest on CritPt (#114 of 115).
Across the 3 benchmarks where at least ten models are scored, qwen3-coder-next is in the top 10% on 0 and in the top half on 0.
Its cheapest listed input price, $0.120 per million tokens, is lower than that of 77% of the 427 models with a listed price.
qwen3-coder-next benchmark results
| Benchmark | Score | Rank | Source | Captured |
|---|---|---|---|---|
| WeirdML | 34.4% | #83 of 109 | Epoch AI Benchmarking Hub | 2026-10-13 |
| SciCode | 32.3% | #89 of 106 | Epoch AI Benchmarking Hub | 2026-10-13 |
| CritPt | 0.0% | #114 of 115 | Epoch AI Benchmarking Hub | 2026-10-13 |
About qwen3-coder-next
qwen3-coder-next is an open-weight model that can run on your own hardware from Alibaba. It was released on 2026-02-02, according to Epoch AI. The cheapest API listing we track charges $0.120 per million input tokens and $0.800 per million output tokens, through openrouter. We hold 3 benchmark results for it across 3 areas, and none is in the top tenth of its board.
Where qwen3-coder-next stands
On our aggregate score, qwen3-coder-next is #575 of 743 ranked models, in the lower half. Its score is 45.5; the scale is centred on 50, so it sits 4.5 points below the typical model. That beats 23% of the ranked field. Among the 74 ranked Alibaba models it is #61. The next one up is qwen3-14b at 45.6. The next one down is qwen1.5-72b-chat at 45.5.
qwen3-coder-next, benchmark by benchmark
qwen3-coder-next lands below the middle on WeirdML: 34.4%, #83 of 109, with 75% of the field scoring higher. GPT-6 Astra (max) leads at 93.3%; the closest result above is Qwen3.6 35B-A3B at 34.5%. It covers unusual machine-learning tasks. The board median is 41.2%, so qwen3-coder-next is 6.8 points below it. Source: Epoch AI Benchmarking Hub, captured 2026-10-13.
SciCode is a weak spot. qwen3-coder-next scores 32.3%, #89 of 106, behind 83% of the models measured. The leader, Claude Opus 5.5 (max), reaches 66.9%. It covers scientific research code. The board median is 44.3%, so qwen3-coder-next is 12.0 points below it. Source: Epoch AI Benchmarking Hub, captured 2026-10-13.
CritPt is a weak spot. qwen3-coder-next scores 0.0%, #114 of 115, behind 98% of the models measured. The leader, GPT-5.6 Sol (max), reaches 32.3%. It covers unpublished research-level physics problems. The board median is 2.9%, so qwen3-coder-next is 2.9 points below it. Source: Epoch AI Benchmarking Hub, captured 2026-10-13.
Strengths and weaknesses
qwen3-coder-next has too few results on boards with ten or more models to say where it is strong or weak. Treat any single score as a data point, not a verdict.
Price and value
The median input price across the 427 priced models is $0.500 per million tokens, so qwen3-coder-next costs less than the typical listing. Models that score within 1.5 points or better and cost less: Qwen2.5-Coder-7B-Instruct ($0.010, 49.5), DeepSeek V4.1 Flash (high) ($0.010, 48.9), Qwen2.5-Coder-3B-Instruct ($0.010, 46.5). Similar scores cost more on Phi-3.5-mini-instruct ($0.130) and Phi-3-mini-128k-instruct ($0.130).
Release history
The Alibaba model released before it was Qwen3-Max-Instruct on 2025-09-24, which scores 48.2. The next one was Qwen3.5 397B-A17B on 2026-02-13, at 51.1.
Reading these numbers
The 3 scores on this page come from 1 source: Epoch AI Benchmarking Hub (3). No official leaderboard supplied any of them, so treat them as third-party measurements. With 3 results the aggregate rank can move a lot when one new score arrives.
Models ranked nearby
- #572 gemini-2.5-flash (45.6)
- #573 qwen3-14b (45.6)
- #574 Yi-1.5-6B-Chat (45.6)
- #576 Qwen1.5-14B-Chat (45.5)
- #577 granite-4.1-30b (45.5)
- #578 Ministral-8B-Instruct-2410 (45.5)
More from Alibaba
- Qwen 3.6 Max (Preview) (#25, 54.1)
- Qwen3.8 Max (xhigh) (#37, 53.2)
- Qwen3.7 Max (#71, 52.3)
- ollama/qwen2.5-coder:32b (#93, 51.9)
- Qwen3 235B A22B diff, no think, Alibaba API (#122, 51.5)
- Qwen2.5-Coder-14B-Instruct (#135, 51.3)
Compare it on the live leaderboard → · How the aggregate score works