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Qwen3 Coder 480B: token counter & pricing

Alibaba · approximate, within ±3% of reference · pricing as of 2026-05-31.

Provider
Alibaba
API model ID
Qwen/Qwen3-Coder-480B-A35B-Instruct
Context window
131,072 tokens
Input price
$2.00 per 1M tokens
Output price
$2.00 per 1M tokens
Tokenizer accuracy
approximate, within ±3% of reference
Pricing as of
2026-05-31

Open the counter to count tokens for Qwen3 Coder 480B in real time.

What is Qwen3 Coder 480B?

Qwen3 Coder 480B is Alibaba's current flagship code-specialized open-weights model, a 480-billion-parameter Mixture-of-Experts model with 35B active parameters, designed specifically for code generation and editing tasks.

$2 input / $2 output per 1M tokens (Together.ai indicative). Single-rate pricing typical of open-weights inference providers.

How tokens are counted here

Qwen uses a custom BPE tokenizer efficient across English and CJK (Chinese, Japanese, Korean). We approximate in your browser, accurate within roughly ±3% for English. CJK accuracy is similar but less thoroughly validated. Marked ≈±3%.

Pricing notes

$2 input / $2 output per 1M (Together.ai). Single-rate, output and input cost the same per token.

For 1,000 input + 200 output: $0.0024 per call, $2,400 per 1M calls.

131,072-token context window.

When to use Qwen3 Coder 480B

When not to use it:

Common questions

Qwen3 Coder 480B vs Claude Sonnet for code?

Sonnet wins on understanding large existing codebases and producing edits that match local conventions. Qwen3 Coder wins on raw greenfield generation benchmarks. Cost: Sonnet $3/$15, Qwen3 Coder $2/$2, Qwen is dramatically cheaper for output-heavy generation. Choose by workload shape.

Same tokenizer as Qwen 2.5 Coder?

Functionally similar (Qwen family tokenizer). Token counts should be within a few percent across versions. The calculator's ≈±3% confidence label applies to both.

Can I self-host?

Yes, but 480B requires substantial hardware, typical inference setup is multi-GPU (8× H100 or similar). For self-hosting, Qwen 2.5 Coder 32B is a more realistic choice; runs on a single 24GB GPU when quantized.

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