Z.ai: GLM 4.7 Flash
z-ai/glm-4.7-flash
Model weightsAs a 30B-class SOTA model, GLM-4.7-Flash offers a new option that balances performance and efficiency. It is further optimized for agentic coding use cases, strengthening coding capabilities, long-horizon task planning, and tool collaboration, and has achieved leading performance among open-source models of the same size on several current public benchmark leaderboards.
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).
| $0.0605 | $0.40 | -- | 0.31s | 43 tok/s | ||
| $0.0700 | $0.40 | $0.01 | 1.09s | 56 tok/s |
- Input $0.0605 / Output $0.4043 tok/s99.25% uptime
- Input $0.07 / Output $0.4056 tok/s18.64% 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
GLM 4.7 Flash — Price history
| $0.0602 | $0.395 | 0.0% | 78.4% | ||
| $0.0478 | $0.396 | 36.6% | 21.6% |
- Effective in $0.0602 / Effective out $0.395Token share78.4%
- Effective in $0.0478 / Effective out $0.396Token share21.6%
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 | GLM-4.7-Flash (Non-reasoning) GPQA Diamond | 45.2% |
| Artificial Analysis | GLM-4.7-Flash (Non-reasoning) HLE | 5.0% |
| Artificial Analysis | GLM-4.7-Flash (Non-reasoning) IFBench | 46.3% |
| Artificial Analysis | GLM-4.7-Flash (Non-reasoning) τ²-Bench Telecom | 91.8% |
| Artificial Analysis | GLM-4.7-Flash (Non-reasoning) AA-LCR | 20.3% |
| Artificial Analysis | GLM-4.7-Flash (Non-reasoning) CritPt | 0.0% |
| Artificial Analysis | GLM-4.7-Flash (Non-reasoning) Terminal-Bench Hard | 3.8% |
| Artificial Analysis | GLM-4.7-Flash (Reasoning) GPQA Diamond | 58.1% |
| Artificial Analysis | GLM-4.7-Flash (Reasoning) HLE | 7.6% |
| Artificial Analysis | GLM-4.7-Flash (Reasoning) IFBench | 60.8% |
| Artificial Analysis | GLM-4.7-Flash (Reasoning) τ²-Bench Telecom | 98.8% |
| Artificial Analysis | GLM-4.7-Flash (Reasoning) AA-LCR | 41.7% |
| Artificial Analysis | GLM-4.7-Flash (Reasoning) CritPt | 0.3% |
| Artificial Analysis | GLM-4.7-Flash (Reasoning) Terminal-Bench Hard | 22.0% |
| Design Arena | GLM 4.7 Flash Models Arena 3D Elo | 1100 |
| Design Arena | GLM 4.7 Flash Models Arena Code Categories Elo | 1167 |
| Design Arena | GLM 4.7 Flash Models Arena Data Visualization Elo | 1120 |
| Design Arena | GLM 4.7 Flash Models Arena Game Development Elo | 1124 |
| Design Arena | GLM 4.7 Flash Models Arena SVG Elo | 1027 |
| Design Arena | GLM 4.7 Flash Models Arena UI Component Elo | 1198 |
| Design Arena | GLM 4.7 Flash Models Arena Website Elo | 1186 |
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
As a 30B-class SOTA model, GLM-4.7-Flash offers a new option that balances performance and efficiency. It is further optimized for agentic coding use cases, strengthening coding capabilities, long-horizon task planning, and tool collaboration, and has achieved leading performance among open-source models of the same size on several current public benchmark leaderboards.
GLM 4.7 Flash costs $0.0605/M input tokens and $0.40/M output tokens.
GLM 4.7 Flash has a 200,000 token context window. It supports up to 131,072 completion tokens.
Yes. GLM 4.7 Flash accepts tools and tool_choice for function calling. It also supports structured outputs via a JSON schema in response_format.
GLM 4.7 Flash is served by 2 providers on OpenRouter: Cloudflare 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.
GLM 4.7 Flash was released on January 19, 2026.