Qwen3.5-27B
by Alibaba (Qwen) · qwen/qwen3.5-27b · #163 cheapest of 325 paid models
Prices updated Jul 22, 2026, 1:31 AM UTC · refreshed hourly
The Qwen3.5 27B native vision-language Dense model incorporates a linear attention mechanism, delivering fast response times while balancing inference speed and performance. Its overall capabilities are comparable to those of...
Compare vs:Claude Sonnet 5Claude Opus 4.6Claude Haiku 4.5GPT-5.6 Sol
Pricing
Input
$0.26
per 1M tokens
Output
$2.60
per 1M tokens
Blended (3:1)
$0.845
3 input : 1 output
Cache read
—
per 1M cached tokens
Cache write
—
per 1M tokens
Cache & batch economics
Effective prices for Qwen3.5-27B (no cache-read rate published — hits billed as normal input).
| Cache hit rate | Effective blended $/1M | Example request* | vs no cache |
|---|---|---|---|
| 0% | $0.845 | $0.0291 | — |
| 50% | $0.845 | $0.0291 | −0% |
| 90% | $0.845 | $0.0291 | −0% |
*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 | $0.00091 | $0.91 |
| Document summary | 8,000 | 1,000 | $0.00468 | $4.68 |
| Codebase question (RAG) | 30,000 | 2,000 | $0.013 | $13.00 |
| Long-context analysis | 150,000 | 5,000 | $0.052 | $52.00 |
Performance
Intelligence Index
33.8
AA composite quality
Coding Index
—
Math Index
—
Agentic Index
—
Output speed
80 tok/s
median
Time to first token
1.31s
median
Time to first answer
26.39s
after reasoning tokens
Artificial Analysis benchmarks
| Benchmark | Score |
|---|---|
| GPQA Diamond | 85.8% |
| Humanity's Last Exam | 22.2% |
| SciCode | 39.5% |
| IFBench | 75.6% |
| AA-LCR (Long Context Reasoning) | 67.3% |
| Terminal-Bench Hard | 32.6% |
| τ²-Bench (Telecom) | 93.9% |
Specs
Context window
262K
tokens
Max output
82K
tokens
Input modalities
text, image, video
Tokenizer
Qwen3