GLM-5.1 - state-of-the-art agentic engineering, now available on DeepInfra!

Qwen3 Coder 480B A35B Instruct is a state-of-the-art large language model developed by the Qwen team at Alibaba Cloud, specifically designed for code generation and agentic coding tasks. It is a Mixture-of-Experts (MoE) model with 480 billion total parameters and 35 billion active parameters per inference, enabling high performance at lower computational cost compared to dense models of similar scale.
The model supports a native context length of 256K tokens (extendable to 1M via YaRN interpolation) and excels in agentic coding, browser-use, and tool-use tasks — achieving results comparable to Claude Sonnet 4. It was trained on 7.5 trillion high-quality tokens with a 70% code ratio across 358 programming languages, and its post-training phase leverages long-horizon reinforcement learning (Agent RL) to improve multi-step planning and interaction with external tools.
Qwen3 Coder 480B A35B Instruct is now available across multiple inference providers — but they’re not created equal. This analysis breaks down which one delivers the best performance, lowest cost, and fastest response times for your use case.
| Provider | Best For | Blended ($/1M) | TTFT (s) | Speed (t/s) | E2E (s) | Context | Func | JSON |
|---|---|---|---|---|---|---|---|---|
| DeepInfra (Turbo, FP4) | Lowest cost + lowest latency; best value for interactive and cost-sensitive apps | $0.41 | 0.60s | 42 | 12.59s | 262k | Yes | No |
| DeepInfra (FP8) | Balanced low latency + mid price; faster throughput than Turbo | $0.70 | 0.87s | 81.1 | 7.04s | 262k | Yes | No |
| Google Vertex | Strong speed/latency balance with JSON mode support | $0.61 | 0.69s | 172.6 | 3.58s | 262k | Yes | Yes |
| Amazon Bedrock | Low price tier with solid throughput; lacks JSON mode | $0.61 | 1.82s | 99.7 | 6.84s | 262k | Yes | No |
| Eigen AI | Maximum throughput; fastest E2E time; lacks function calling | $0.61 | 1.32s | 265.7 | 3.20s | 262k | No | Yes |
Based on benchmarks across 10 tracked providers, DeepInfra (Turbo, FP4) is the recommended API for production-scale Qwen3 Coder 480B deployment. It offers the lowest blended price ($0.41/1M), tied-lowest TTFT (0.60s), and full Function Calling support. For teams requiring higher throughput, DeepInfra (FP8) at $0.70/1M provides a strong step up to 81.1 t/s. For maximum raw speed with JSON mode, Google Vertex at $0.61/1M delivers 172.6 t/s and 0.69s TTFT.
DeepInfra (Turbo, FP4) offers the strongest overall balance of latency, cost, and feature support for Qwen3 Coder 480B deployments.
The Turbo FP4 variant’s near-instantaneous response (0.60s TTFT) makes it ideal for interactive coding assistants and real-time agentic workflows. Its pricing undercuts the next cheapest option (Novita at $0.55) by 25%, making it the strongest choice for cost-sensitive production workloads. The trade-off is lower throughput (42 t/s) and no JSON mode — developers requiring structured outputs should opt for DeepInfra FP8 or Google Vertex.
DeepInfra (FP8) provides a meaningful throughput upgrade over the Turbo variant at a moderate price increase.
At $0.70/1M, DeepInfra FP8 sits in the middle of the pricing range while delivering nearly double the throughput of the Turbo variant. Its 7.04s E2E time is considerably faster than the Turbo’s 12.59s, making it the better choice for workloads that mix interactive use with moderate content generation volume.
Google Vertex offers the best combination of speed, latency, and full API feature support among the competitive mid-price tier.
Google Vertex is the only provider in the $0.61 price tier that combines low latency (0.69s), high throughput (172.6 t/s), and full feature support including JSON mode. For teams requiring structured output alongside fast generation, it is the strongest alternative to DeepInfra.
Eigen AI leads the benchmark on raw generation speed, delivering the fastest E2E response times of any provider.
Eigen AI’s 265.7 t/s throughput makes it the fastest provider for bulk code generation and long-form content. However, the absence of Function Calling makes it unsuitable for agentic workflows where the model needs to invoke external tools. It is best suited for high-volume batch generation where tool use is not required.
Amazon Bedrock offers competitive pricing (tied lowest input at $0.22/1M) and solid throughput (99.7 t/s), but its 1.82s TTFT is one of the higher latency figures in the benchmark and it lacks JSON mode. It is recommended only when strict AWS IAM or compliance requirements make it the necessary choice.
For Qwen3 Coder 480B A35B Instruct deployments, DeepInfra is the recommended provider across both its available variants — with the right choice depending on your workload priorities.
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