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Qwen3-Coder-480B-A35B-Instruct-Turbo

deepinfra · chat model

Qwen3-Coder-480B-A35B-Instruct-Turbo is listed here as a chat model from deepinfra. This page shows simple API pricing, token limits, and capability flags so you can compare it with similar options.

Input
$0.2900 / 1M tokens
Output
$1.2000 / 1M tokens
Cached input
N/A
Context
262.1K

Quick read

Best for

Use this page when you need a fast view of cost, context size, and supported features before testing the model in your own workload.

Things to verify

Always check the provider page for discounts, cache pricing, region rules, and any model limits that may not appear in public metadata.

Pricing

Item Price
Input
$0.2900 / 1M tokens
Output
$1.2000 / 1M tokens
Embedding
$0.2900 / 1M tokens

Token limits

Context window
262.1K
Max input tokens
262.1K
Max output tokens
262.1K
Max tokens
262.1K

Capabilities

Capability Supported
Vision
Function calling
Parallel function calling
Tool choice
Prompt caching
Reasoning
Response schema
System messages
Audio input
Audio output
Web search
PDF input
Video input

Benchmarks

Most benchmark rows are attached to the base model family rather than this provider route. Open benchmark explorer

Benchmark Score Metric Scope Checked Source
Terminal-Bench 2.0 23.9 * score Base model: Qwen3-Coder (Qwen3-Coder-480B-A35B-Instruct) 2026-05-31 Link
SWE-bench Pro 38.7 score Base model: Qwen3-Coder (Qwen3-Coder-480B-A35B-Instruct) 2026-05-31 Link
Evasion Bench 78.16 score Base model: Qwen3-Coder (Qwen3-Coder-480B-A35B-Instruct) 2026-05-31 Link
Artificial Analysis Intelligence Index 24.8 score Base model: qwen3-coder (qwen/qwen3-coder) 2026-05-31 Link
Artificial Analysis Coding Index 24.6 score Base model: qwen3-coder (qwen/qwen3-coder) 2026-05-31 Link
Artificial Analysis Agentic Index 18.3 score Base model: qwen3-coder (qwen/qwen3-coder) 2026-05-31 Link

Sources

Source links
Pricing data LiteLLM model cost map
Synced at 2026-05-28

Docs

Official docs

Similar models

This list is ranked by overall similarity. Use filters to emphasize the lens that matters most for the replacement you are making.

Comparing from
Model Cost Input shape Features Context Why it is close
Qwen3-Coder-480B-A35B-Instruct-Turbo
deepinfra
In $0.2900 / 1M tokens
Out $1.2000 / 1M tokens
text
Output: text
Function callingTool choice
262.1K
Current model
Reference row

Overall blends cost, modality overlap, capabilities, and context.

Model Cost Input shape Features Context Why it is close
qwen3-coder
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In $0.2200 / 1M tokens
Out $0.9500 / 1M tokens
text
Output: text
Function callingTool choice
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Qwen3-Coder-480B-A35B-Instruct
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In $0.4000 / 1M tokens
Out $1.6000 / 1M tokens
text
Output: text
Function callingTool choice
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Qwen3-Next-80B-A3B-Instruct
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In $0.1400 / 1M tokens
Out $1.4000 / 1M tokens
text
Output: text
Function callingTool choice
262.1K
Same provider
Overall 94%
Qwen3-Next-80B-A3B-Thinking
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In $0.1400 / 1M tokens
Out $1.4000 / 1M tokens
text
Output: text
Function callingTool choice
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Overall 94%
Qwen3-235B-A22B-Thinking-2507
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In $0.3000 / 1M tokens
Out $2.9000 / 1M tokens
text
Output: text
Function callingTool choice
262.1K
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Overall 93%
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In $0.2700 / 1M tokens
Out $1.0000 / 1M tokens
text
Output: text
Function callingTool choice
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In $0.5000 / 1M tokens
Out $2.0000 / 1M tokens
text
Output: text
Function callingTool choice
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In $0.2500 / 1M tokens
Out $0.8800 / 1M tokens
text
Output: text
Function callingTool choice
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Overall 90%
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In $0.3800 / 1M tokens
Out $0.8900 / 1M tokens
text
Output: text
Function callingTool choice
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Out $1.1000 / 1M tokens
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Output: text
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In $0.3000 / 1M tokens
Out $0.9000 / 1M tokens
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In $0.5000 / 1M tokens
Out $1.5000 / 1M tokens
text
Output: text
Function callingTool choice
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Overall 79%
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In $0.5000 / 1M tokens
Out $1.5000 / 1M tokens
text
Output: text
Function callingTool choice
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Overall 79%
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In $0.3000 / 1M tokens
Out $1.2000 / 1M tokens
text
Output: text
Function callingTool choice
8.2K
Text covered
Overall 77%
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Bedrock
In $0.3000 / 1M tokens
Out $1.2000 / 1M tokens
text
Output: text
Function callingTool choice
8.2K
Text covered
Overall 77%
minimax.minimax-m2.1
Bedrock
In $0.3000 / 1M tokens
Out $1.2000 / 1M tokens
text
Output: text
Function callingTool choice
8.2K
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Overall 77%
minimax.minimax-m2.1
Bedrock
In $0.3000 / 1M tokens
Out $1.2000 / 1M tokens
text
Output: text
Function callingTool choice
8.2K
Text covered
Overall 77%
minimax.minimax-m2.5
Bedrock
In $0.3000 / 1M tokens
Out $1.2000 / 1M tokens
text
Output: text
Function callingTool choice
8.2K
Text covered
Overall 77%
Llama-3.3-70B-Instruct
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In $0.7100 / 1M tokens
Out $0.7100 / 1M tokens
text
Output: text
Function callingTool choice
2.0K
Text covered
Overall 75%
Phi-4
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In $0.1250 / 1M tokens
Out $0.5000 / 1M tokens
text
Output: text
Function callingTool choice
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Text covered
Overall 74%
minimax.minimax-m2.5
Bedrock
In $0.3000 / 1M tokens
Out $1.2000 / 1M tokens
text
Output: text
Function callingTool choice
8.2K
Text covered
Overall 73%
gpt-35-turbo-16k-0613
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In $3.0000 / 1M tokens
Out $4.0000 / 1M tokens
text
Output: text
Function callingTool choice
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Text covered
Overall 69%
gpt-4-0613
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In $30.0000 / 1M tokens
Out $60.0000 / 1M tokens
text
Output: text
Function callingTool choice
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Overall 66%