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Qwen2.5-VL-32B-Instruct

deepinfra · chat model

Qwen2.5-VL-32B-Instruct 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
$0.2000 / 1M tokens
Output
$0.6000 / 1M tokens
Cached input
N/A
Context
128.0K
Compare similar models Open a side-by-side table using this route and the closest match from the current catalog. Estimate workload cost Use token counts, request volume, and cache assumptions to check a realistic monthly bill. Explore benchmark family Review source-backed benchmark rows for the attached base model family. Check data sources See how pricing data is generated and what still needs provider verification.

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
$0.2000 / 1M tokens
Output
$0.6000 / 1M tokens
Embedding
$0.2000 / 1M tokens

Token limits

Context window
128.0K
Max input tokens
128.0K
Max output tokens
128.0K
Max tokens
128.0K

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
MMLU 74.2% accuracy Base model: Qwen2.5 (Qwen2.5-7B-Instruct) 2026-05-31 Link
MMLU 83.3% accuracy Base model: Qwen2.5 (Qwen2.5-32B-Instruct) 2026-05-31 Link
MATH 49.8% accuracy Base model: Qwen2.5 (Qwen2.5-7B-Instruct) 2026-05-31 Link
MATH 57.7% accuracy Base model: Qwen2.5 (Qwen2.5-32B-Instruct) 2026-05-31 Link
HumanEval 57.9% pass@1 Base model: Qwen2.5 (Qwen2.5-7B-Instruct) 2026-05-31 Link
HumanEval 58.5% pass@1 Base model: Qwen2.5 (Qwen2.5-32B-Instruct) 2026-05-31 Link
Artificial Analysis Coding Index 11.9 score Base model: qwen2.5 (qwen/qwen-2.5-72b-instruct) 2026-05-31 Link
GPQA Diamond 49.1% accuracy Base model: qwen2.5 (qwen/qwen-2.5-72b-instruct) 2026-05-31 Link
Humanity's Last Exam 4.2% accuracy Base model: qwen2.5 (qwen/qwen-2.5-72b-instruct) 2026-05-31 Link
IFBench 36.9% accuracy Base model: qwen2.5 (qwen/qwen-2.5-72b-instruct) 2026-05-31 Link
SciCode 26.7% accuracy Base model: qwen2.5 (qwen/qwen-2.5-72b-instruct) 2026-05-31 Link
MMMU 70 score Base model: Qwen2.5-VL (Qwen2.5-VL-32B) 2026-05-31 Link
MMMU-Pro 49.5 score Base model: Qwen2.5-VL (Qwen2.5-VL-32B) 2026-05-31 Link
MMStar 69.5 score Base model: Qwen2.5-VL (Qwen2.5-VL-32B) 2026-05-31 Link
MathVista 74.7 score Base model: Qwen2.5-VL (Qwen2.5-VL-32B) 2026-05-31 Link
MathVision 40.0 score Base model: Qwen2.5-VL (Qwen2.5-VL-32B) 2026-05-31 Link
CC-OCR 77.1 score Base model: Qwen2.5-VL (Qwen2.5-VL-32B) 2026-05-31 Link
DocVQA 94.8 score Base model: Qwen2.5-VL (Qwen2.5-VL-32B) 2026-05-31 Link
InfoVQA 83.4 score Base model: Qwen2.5-VL (Qwen2.5-VL-32B) 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
Qwen2.5-VL-32B-Instruct
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In $0.2000 / 1M tokens
Out $0.6000 / 1M tokens
imagetext
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Current model
Reference row

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

Model Cost Input shape Features Context Why it is close
mistral-small-2503
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In $0.1000 / 1M tokens
Out $0.3000 / 1M tokens
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Overall 90%
ministral-3b-2512
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In $0.1000 / 1M tokens
Out $0.1000 / 1M tokens
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VisionFunction callingTool choice
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ministral-14b-2512
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In $0.2000 / 1M tokens
Out $0.2000 / 1M tokens
imagetext
Output: text
VisionFunction callingTool choice
262.1K
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Overall 85%
Llama-4-Scout-17B-16E-Instruct
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In $0.2000 / 1M tokens
Out $0.7800 / 1M tokens
imagetext
Output: text
VisionFunction callingTool choice
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Text + image covered
Overall 84%
pixtral-12b-2409
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In $0.1500 / 1M tokens
Out $0.1500 / 1M tokens
imagetext
Output: text
VisionFunction callingTool choice
128.0K
Text + image covered
Overall 83%
grok-4-fast-non-reasoning
azure_ai
In $0.2000 / 1M tokens
Out $0.5000 / 1M tokens
imagetext
Output: text
Function callingTool choice
131.1K
Text + image covered
Overall 83%
Mistral-Small-3.2-24B-Instruct-2506
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In $0.0750 / 1M tokens
Out $0.2000 / 1M tokens
imagetext
Output: text
Function callingTool choice
128.0K
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Overall 79%
gemma-3-27b-it
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In $0.0900 / 1M tokens
Out $0.1600 / 1M tokens
imagetext
Output: text
Function callingTool choice
131.1K
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Overall 78%
claude-3-haiku
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In $0.2500 / 1M tokens
Out $1.2500 / 1M tokens
imagetext
Output: text
VisionFunction callingTool choice
4.1K
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Overall 78%
llama-3.2-90b
vercel_ai_gateway
In $0.7200 / 1M tokens
Out $0.7200 / 1M tokens
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Output: text
VisionFunction callingTool choice
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Text + image covered
Overall 78%
Llama-3.2-11B-Vision-Instruct
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In $0.3700 / 1M tokens
Out $0.3700 / 1M tokens
imagetext
Output: text
VisionFunction callingTool choice
2.0K
Text + image covered
Overall 77%
Llama-4-Maverick-17B-128E-Instruct-FP8
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In $0.1500 / 1M tokens
Out $0.6000 / 1M tokens
imagetext
Output: text
Function callingTool choice
1.0M
Same provider
Overall 76%
gemma-3-12b-it
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In $0.0500 / 1M tokens
Out $0.1000 / 1M tokens
imagetext
Output: text
Function callingTool choice
131.1K
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Overall 75%
Llama-4-Maverick-17B-128E-Instruct-FP8
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In $1.4100 / 1M tokens
Out $0.3500 / 1M tokens
imagetext
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Overall 75%
gemma-3-4b-it
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In $0.0400 / 1M tokens
Out $0.0800 / 1M tokens
imagetext
Output: text
Function callingTool choice
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Llama-3.3-70B-Instruct
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In $0.2300 / 1M tokens
Out $0.4000 / 1M tokens
imagetext
Output: text
Function callingTool choice
131.1K
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Overall 74%
Missing image
mistral-large-3
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In $0.5000 / 1M tokens
Out $1.5000 / 1M tokens
imagetext
Output: text
VisionFunction callingTool choice
8.2K
Text + image covered
Overall 74%
claude-3-haiku@20240307
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In $0.2500 / 1M tokens
Out $1.2500 / 1M tokens
imagetext code
Output: text
VisionFunction callingTool choice
4.1K
Text + image covered
Overall 70%
Llama-3.2-90B-Vision-Instruct
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In $2.0400 / 1M tokens
Out $2.0400 / 1M tokens
imagetext
Output: text
VisionFunction callingTool choice
2.0K
Text + image covered
Overall 69%
DeepSeek-R1-Distill-Llama-70B
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In $0.2000 / 1M tokens
Out $0.6000 / 1M tokens
imagetext
Output: text
Low overlap
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Missing image
deepseek-v3-0324
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Out $0.6000 / 1M tokens
imagetext
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Missing text, image
deepseek-llama3.3-70b
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In $0.2000 / 1M tokens
Out $0.6000 / 1M tokens
imagetext
Output: unknown
Function callingTool choice
131.1K
Partial I/O overlap
Overall 43%
Missing text, image
deepseek-r1-0528
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In $0.2000 / 1M tokens
Out $0.6000 / 1M tokens
imagetext
Output: unknown
Function callingTool choice
131.1K
Partial I/O overlap
Overall 43%
Missing text, image
llama-4-maverick-17b-128e-instruct
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In $0.2000 / 1M tokens
Out $0.6000 / 1M tokens
imagetext
Output: unknown
VisionFunction callingTool choice
8.2K
Partial I/O overlap
Overall 40%
Missing text, image
Qwen3-235B-A22B
nebius
In $0.2000 / 1M tokens
Out $0.6000 / 1M tokens
imagetext
Output: unknown
Function calling
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Partial I/O overlap
Overall 36%
Missing text, image