Qwen3 Coder Next
by Alibaba (Qwen) · qwen/qwen3-coder-next · #83 cheapest of 325 paid models
Prices updated Jul 22, 2026, 1:37 AM UTC · refreshed hourly
Qwen3-Coder-Next is an open-weight causal language model optimized for coding agents and local development workflows. It uses a sparse MoE design with 80B total parameters and only 3B activated per...
Compare vs:Claude Sonnet 5Claude Opus 4.6Claude Haiku 4.5GPT-5.6 Sol
Pricing
Input
$0.11
per 1M tokens
Output
$0.80
per 1M tokens
Blended (3:1)
$0.282
3 input : 1 output
Cache read
$0.07
per 1M cached tokens
Cache write
—
per 1M tokens
Cache & batch economics
Effective prices for Qwen3 Coder Next with prompt caching.
| Cache hit rate | Effective blended $/1M | Example request* | vs no cache |
|---|---|---|---|
| 0% | $0.282 | $0.012 | — |
| 50% | $0.267 | $0.01 | −17% |
| 90% | $0.256 | $0.00842 | −30% |
*Example: 100K sticky context + 2K new input + 1K output. Batch discount is an approximate 50% off list rates (available for OpenAI / Anthropic / Google — not flagged for this creator). Confirm on the vendor’s pricing page.
What a request costs
| Workload | Input tokens | Output tokens | Cost / request | Cost / 1K requests |
|---|---|---|---|---|
| Short chat message | 500 | 300 | $0.000295 | $0.295 |
| Document summary | 8,000 | 1,000 | $0.00168 | $1.68 |
| Codebase question (RAG) | 30,000 | 2,000 | $0.0049 | $4.90 |
| Long-context analysis | 150,000 | 5,000 | $0.0205 | $20.50 |
Performance
Intelligence Index
21.1
AA composite quality
Coding Index
36.2
Math Index
—
Agentic Index
8.8
Output speed
96 tok/s
median
Time to first token
1.07s
median
Time to first answer
1.07s
after reasoning tokens
Artificial Analysis benchmarks
| Benchmark | Score |
|---|---|
| GPQA Diamond | 73.7% |
| Humanity's Last Exam | 9.3% |
| SciCode | 32.3% |
| IFBench | 35.2% |
| AA-LCR (Long Context Reasoning) | 40.0% |
| Terminal-Bench Hard | 18.2% |
| Terminal-Bench 2.1 | 38.2% |
| τ²-Bench (Telecom) | 79.5% |
| τ³-Bench Banking | 5.2% |
Specs
Context window
262K
tokens
Max output
262K
tokens
Input modalities
text
Tokenizer
Qwen