
Qwen: Qwen3 30B A3B Instruct 2507
qwen/qwen3-30b-a3b-instruct-2507
Model weightsQwen3-30B-A3B-Instruct-2507 is a 30.5B-parameter mixture-of-experts language model from Qwen, with 3.3B active parameters per inference. It operates in non-thinking mode and is designed for high-quality instruction following, multilingual understanding, and agentic tool use. Post-trained on instruction data, it demonstrates competitive performance across reasoning (AIME, ZebraLogic), coding (MultiPL-E, LiveCodeBench), and alignment (IFEval, WritingBench) benchmarks. It outperforms its non-instruct variant on subjective and open-ended tasks while retaining strong factual and coding performance.
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).
| $0.09 | $0.30 | -- | 0.46s | 64 tok/s | ||
| $0.09 | $0.30 | -- | 1.16s | 36 tok/s | ||
| $0.10 | $0.30 | $0.10 | 0.27s | 54 tok/s |
- Input $0.09 / Output $0.3064 tok/s94.39% uptime
- Input $0.09 / Output $0.3036 tok/s98.58% uptime
- Input $0.10 / Output $0.3054 tok/s96.56% 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 30B A3B Instruct 2507 — Price history
| $0.0899 | $0.297 | 75.7% | 11.9% | ||
| $0.0900 | $0.296 | 77.0% | 47.8% | ||
| $0.0998 | $0.297 | 50.3% | 40.4% |
- Effective in $0.0899 / Effective out $0.297Token share11.9%
- Effective in $0.0900 / Effective out $0.296Token share47.8%
- Effective in $0.0998 / Effective out $0.297Token share40.4%
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 30B A3B 2507 Instruct GPQA Diamond | 65.9% |
| Artificial Analysis | Qwen3 30B A3B 2507 Instruct HLE | 6.9% |
| Artificial Analysis | Qwen3 30B A3B 2507 Instruct IFBench | 33.1% |
| Artificial Analysis | Qwen3 30B A3B 2507 Instruct τ²-Bench Telecom | 10.2% |
| Artificial Analysis | Qwen3 30B A3B 2507 Instruct AA-LCR | 26.3% |
| Artificial Analysis | Qwen3 30B A3B 2507 Instruct CritPt | 0.0% |
| Artificial Analysis | Qwen3 30B A3B 2507 Instruct LiveCodeBench | 51.5% |
| Artificial Analysis | Qwen3 30B A3B 2507 Instruct Terminal-Bench Hard | 6.1% |
| Artificial Analysis | Qwen3 30B A3B 2507 Instruct MMLU-Pro | 77.7% |
| Artificial Analysis | Qwen3 30B A3B 2507 Instruct AIME 2025 | 66.3% |
| Artificial Analysis | Qwen3 30B A3B 2507 Instruct AIME | 72.7% |
| Artificial Analysis | Qwen3 30B A3B 2507 Instruct MATH-500 | 97.5% |
| Artificial Analysis | Qwen3 30B A3B (Non-reasoning) GPQA Diamond | 51.5% |
| Artificial Analysis | Qwen3 30B A3B (Non-reasoning) HLE | 4.6% |
| Artificial Analysis | Qwen3 30B A3B (Non-reasoning) IFBench | 31.9% |
| Artificial Analysis | Qwen3 30B A3B (Non-reasoning) τ²-Bench Telecom | 22.2% |
| Artificial Analysis | Qwen3 30B A3B (Non-reasoning) AA-LCR | 0.0% |
| Artificial Analysis | Qwen3 30B A3B (Non-reasoning) CritPt | 0.0% |
| Artificial Analysis | Qwen3 30B A3B (Non-reasoning) LiveCodeBench | 32.2% |
| Artificial Analysis | Qwen3 30B A3B (Non-reasoning) Terminal-Bench Hard | 6.8% |
| Artificial Analysis | Qwen3 30B A3B (Non-reasoning) MMLU-Pro | 71.0% |
| Artificial Analysis | Qwen3 30B A3B (Non-reasoning) AIME 2025 | 21.7% |
| Artificial Analysis | Qwen3 30B A3B (Non-reasoning) AIME | 26.0% |
| Artificial Analysis | Qwen3 30B A3B (Non-reasoning) MATH-500 | 86.3% |
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
Qwen3-30B-A3B-Instruct-2507 is a 30.5B-parameter mixture-of-experts language model from Qwen, with 3.3B active parameters per inference. It operates in non-thinking mode and is designed for high-quality instruction following, multilingual understanding, and agentic tool use.
Qwen3 30B A3B Instruct 2507 costs $0.09/M input tokens and $0.30/M output tokens.
Qwen3 30B A3B Instruct 2507 has a 262,144 token context window.
Yes. Qwen3 30B A3B Instruct 2507 accepts tools and tool_choice for function calling. It also supports structured outputs via a JSON schema in response_format.
Qwen3 30B A3B Instruct 2507 is served by 3 providers on OpenRouter: DekaLLM, SiliconFlow, and Nebius Token Factory. 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 30B A3B Instruct 2507 was released on July 29, 2025. Its knowledge cutoff is June 30, 2025.