
Qwen: Qwen3.5-27B
qwen/qwen3.5-27b
Model weightsThe 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 the Qwen3.5-122B-A10B.
Providers
Different companies host the same model. OpenRouter routes your request to one of them based on the routing mode you pick: Balanced (price + speed), Nitro (fastest), or Floor (cheapest).
| $0.260 | $2.60 | -- | 0.39s | 74 tok/s | ||
| $0.270 | $2.16 | $0.27 | 1.50s | 36 tok/s | ||
| $0.250 | $2.00 | -- | 4.45s | 19 tok/s | ||
| $0.200 | $1.75 | $0.02 | 4.01s | 36 tok/s | ||
| $0.300 | $2.40 | -- | 3.08s | 21 tok/s | ||
| $0.195 | $1.56 | -- | 4.27s | 62 tok/s |
Input $0.26 / Output $2.6074 tok/s99.76% uptime- Input $0.27 / Output $2.1636 tok/s99.55% uptime
- Input $0.25 / Output $2.0019 tok/s95.53% uptime
- Input $0.20 / Output $1.7536 tok/s87.41% uptime
- Input $0.30 / Output $2.4021 tok/s100.00% uptime
- Input $0.195 / Output $1.5662 tok/s91.66% uptime
Pricing
The average price customers actually pay for this model, next to the prices providers post. Caching and discounts mean the price actually paid is often well below the listed one.
Weighted average
Qwen3.5-27B — Price history
| $0.134 | $1.75 | 36.6% | 1.4% | ||
| $0.195 | $1.56 | 0.0% | 20.8% | ||
| $0.250 | $2.00 | 0.0% | 0.3% | ||
| $0.260 | $2.60 | 0.0% | 5.1% | ||
| $0.270 | $2.16 | 0.0% | 1.2% | ||
| $0.300 | $2.40 | 0.0% | 71.3% |
- Effective in $0.134 / Effective out $1.75Token share1.4%
- Effective in $0.195 / Effective out $1.56Token share20.8%
- Effective in $0.250 / Effective out $2.00Token share0.3%
- Effective in $0.260 / Effective out $2.60Token share5.1%
- Effective in $0.270 / Effective out $2.16Token share1.2%
- Effective in $0.300 / Effective out $2.40Token share71.3%
Performance
Throughput is how fast the model writes (tokens per second — higher is better). Latency is total round-trip time (lower is better). TTFT is time-to-first-token — how long before you see anything appear (lower is better).
P50, best across providers
P50, best provider
Uptime
Uptime is the percentage of the past 3 days that at least one provider was responding to requests. Availability is the percentage of time that inference was successfully served. OpenRouter continuously monitors and uses the next-best provider when one returns an error.
Availability over the last 3 days
Last 72 hoursAvailability over the last 24 hours
When an error occurs in an upstream provider, we can recover by routing to another healthy provider, if your request filters allow it. You can access per-provider uptime data programmatically through the Endpoints API. Learn more about our load balancing and provider routing options.
Benchmarks
Scores on standardized evaluations and this model’s own outputs on shared benchmark prompts. Higher percentages are better — and each rank shows where this model lands among the models evaluated on that source.
| Source | Benchmark | Score |
|---|---|---|
| Artificial Analysis | Qwen3.5 27B (Reasoning) GPQA Diamond | 85.8% |
| Artificial Analysis | Qwen3.5 27B (Reasoning) HLE | 23.9% |
| Artificial Analysis | Qwen3.5 27B (Reasoning) IFBench | 75.6% |
| Artificial Analysis | Qwen3.5 27B (Reasoning) τ²-Bench Telecom | 93.9% |
| Artificial Analysis | Qwen3.5 27B (Reasoning) AA-LCR | 77.7% |
| Artificial Analysis | Qwen3.5 27B (Reasoning) CritPt | 0.9% |
| Artificial Analysis | Qwen3.5 27B (Reasoning) Terminal-Bench Hard | 32.6% |
| Artificial Analysis | Qwen3.5 27B (Non-reasoning) GPQA Diamond | 84.2% |
| Artificial Analysis | Qwen3.5 27B (Non-reasoning) HLE | 13.9% |
| Artificial Analysis | Qwen3.5 27B (Non-reasoning) IFBench | 46.9% |
| Artificial Analysis | Qwen3.5 27B (Non-reasoning) τ²-Bench Telecom | 87.1% |
| Artificial Analysis | Qwen3.5 27B (Non-reasoning) AA-LCR | 64.0% |
| Artificial Analysis | Qwen3.5 27B (Non-reasoning) CritPt | 0.3% |
| Artificial Analysis | Qwen3.5 27B (Non-reasoning) Terminal-Bench Hard | 31.8% |
Apps
Public apps that send the most traffic to this model. Good signal for what real production workloads look like — and a hint at which use cases this model is best suited for.
Activity
Token volume and request traffic to this model over time.
API
Drop-in code to call this model. OpenRouter's API is OpenAI-compatible — most SDKs work by just swapping the base URL. The only thing that changes between models is the model slug below.
Not currently available through EU in-region routing. In-region routing docs
Frequently asked questions
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 the Qwen3.5-122B-A10B.
Qwen3.5-27B costs $0.195/M input tokens and $1.56/M output tokens.
Qwen3.5-27B has a 262,144 token context window. It supports up to 65,536 completion tokens.
Yes. Qwen3.5-27B accepts tools and tool_choice for function calling. It also supports structured outputs via a JSON schema in response_format.
Qwen3.5-27B accepts text, images, and video as input and returns text.
Qwen3.5-27B is served by 6 providers on OpenRouter: Alibaba Cloud Int., Chutes, SiliconFlow, DeepInfra, AtlasCloud, and NovitaAI. Requests are routed to the best available provider, with automatic failover to the others, and you can pin or exclude providers with provider routing.
Qwen3.5-27B was released on February 25, 2026.