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deepseek.v3.2

bedrock_converse · chat model

deepseek.v3.2 is listed here as a chat model from bedrock_converse. This page shows simple API pricing, token limits, and capability flags so you can compare it with similar options.

Input
$0.6200 / 1M tokens
Output
$1.8500 / 1M tokens
Cached input
N/A
Context
163.8K
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
$0.6200 / 1M tokens
Output
$1.8500 / 1M tokens
Embedding
$0.6200 / 1M tokens

Token limits

Context window
163.8K
Max input tokens
163.8K
Max output tokens
163.8K
Max tokens
163.8K

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 88.5 EM Base model: DeepSeek-V3 (DeepSeek-V3) 2026-05-31 Link
GPQA Diamond 59.1 Pass@1 Base model: DeepSeek-V3 (DeepSeek-V3) 2026-05-31 Link
LiveCodeBench 37.6 Pass@1 Base model: DeepSeek-V3 (DeepSeek-V3) 2026-05-31 Link
AIME 2024 39.2 Pass@1 Base model: DeepSeek-V3 (DeepSeek-V3) 2026-05-31 Link
MATH-500 90.2 EM Base model: DeepSeek-V3 (DeepSeek-V3) 2026-05-31 Link
Aider Polyglot 74.2% percent correct Base model: DeepSeek V3.2-Exp (deepseek/deepseek-reasoner) 2026-05-31 Link
MMLU-Pro 85.0 EM Base model: DeepSeek-V3.2-Exp (DeepSeek-V3.2-Exp) 2026-05-31 Link
GPQA Diamond 79.9 pass@1 Base model: DeepSeek-V3.2-Exp (DeepSeek-V3.2-Exp) 2026-05-31 Link
LiveCodeBench 74.1 pass@1 Base model: DeepSeek-V3.2-Exp (DeepSeek-V3.2-Exp) 2026-05-31 Link
AIME 2025 89.3 pass@1 Base model: DeepSeek-V3.2-Exp (DeepSeek-V3.2-Exp) 2026-05-31 Link
Aider Polyglot 74.5 accuracy Base model: DeepSeek-V3.2-Exp (DeepSeek-V3.2-Exp) 2026-05-31 Link
SWE-bench Verified 67.8 resolved Base model: DeepSeek-V3.2-Exp (DeepSeek-V3.2-Exp) 2026-05-31 Link
Terminal-Bench 37.7 score Base model: DeepSeek-V3.2-Exp (DeepSeek-V3.2-Exp) 2026-05-31 Link
Diamond 82.4 score Base model: DeepSeek-V3.2 (deepseek-ai/DeepSeek-V3.2) 2026-05-31 Link
Terminal-Bench 2.0 39.6 * score Base model: DeepSeek-V3.2 (deepseek-ai/DeepSeek-V3.2) 2026-05-31 Link
Apex Agents 7 * score Base model: DeepSeek-V3.2 (deepseek-ai/DeepSeek-V3.2) 2026-05-31 Link
SWE-bench Pro 15.56 score Base model: DeepSeek-V3.2 (deepseek-ai/DeepSeek-V3.2) 2026-05-31 Link
SWE-bench Verified 70 * resolved Base model: DeepSeek-V3.2 (deepseek-ai/DeepSeek-V3.2) 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
deepseek.v3.2
bedrock_converse
In $0.6200 / 1M tokens
Out $1.8500 / 1M tokens
text
Output: text
Function callingTool choiceReasoning
163.8K
Current model
Reference row

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

Model Cost Input shape Features Context Why it is close
deepseek.v3.2
Bedrock
In $0.6200 / 1M tokens
Out $1.8500 / 1M tokens
text
Output: text
Function callingTool choiceReasoning
163.8K
Text covered
Overall 100%
deepseek.v3.2
Bedrock
In $0.6200 / 1M tokens
Out $1.8500 / 1M tokens
text
Output: text
Function callingTool choiceReasoning
163.8K
Text covered
Overall 100%
deepseek.v3.2
Bedrock
In $0.6200 / 1M tokens
Out $1.8500 / 1M tokens
text
Output: text
Function callingTool choiceReasoning
163.8K
Text covered
Overall 100%
deepseek.v3.2
Bedrock
In $0.7400 / 1M tokens
Out $2.2200 / 1M tokens
text
Output: text
Function callingTool choiceReasoning
163.8K
Text covered
Overall 97%
deepseek.v3.2
Bedrock
In $0.7400 / 1M tokens
Out $2.2200 / 1M tokens
text
Output: text
Function callingTool choiceReasoning
163.8K
Text covered
Overall 97%
deepseek.v3.2
Bedrock
In $0.7400 / 1M tokens
Out $2.2200 / 1M tokens
text
Output: text
Function callingTool choiceReasoning
163.8K
Text covered
Overall 97%
deepseek.v3.2
Bedrock
In $0.7400 / 1M tokens
Out $2.2200 / 1M tokens
text
Output: text
Function callingTool choiceReasoning
163.8K
Text covered
Overall 97%
deepseek.v3.2
Bedrock
In $0.7400 / 1M tokens
Out $2.2200 / 1M tokens
text
Output: text
Function callingTool choiceReasoning
163.8K
Text covered
Overall 97%
deepseek.v3-v1:0
bedrock_converse
In $0.5800 / 1M tokens
Out $1.6800 / 1M tokens
text
Output: text
Function callingTool choiceReasoning
81.9K
Same provider
Overall 91%
qwen.qwen3-235b-a22b-2507-v1:0
bedrock_converse
In $0.2200 / 1M tokens
Out $0.8800 / 1M tokens
text
Output: text
Function callingTool choiceReasoning
131.1K
Same provider
Overall 85%
qwen.qwen3-coder-480b-a35b-v1:0
bedrock_converse
In $0.2200 / 1M tokens
Out $1.8000 / 1M tokens
text
Output: text
Function callingTool choiceReasoning
65.5K
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Overall 85%
Phi-4-reasoning
azure_ai
In $0.1250 / 1M tokens
Out $0.5000 / 1M tokens
text
Output: text
Function callingTool choiceReasoning
4.1K
Text covered
Overall 70%
nvidia.nemotron-super-3-120b
bedrock_converse
In $0.1500 / 1M tokens
Out $0.6500 / 1M tokens
text
Output: text
Function callingTool choiceReasoning
32.8K
Same provider
Overall 68%
minimax.minimax-m2.1
bedrock_converse
In $0.3000 / 1M tokens
Out $1.2000 / 1M tokens
text
Output: text
Function callingTool choice
8.2K
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Overall 65%
minimax.minimax-m2.5
bedrock_converse
In $0.3000 / 1M tokens
Out $1.2000 / 1M tokens
text
Output: text
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8.2K
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Overall 65%
us.deepseek.v3.2
bedrock_converse
In $0.6200 / 1M tokens
Out $1.8500 / 1M tokens
text
Output: unknown
Function callingTool choiceReasoning
163.8K
Same provider
Overall 60%
Missing text
Llama-4-Maverick-17B-128E-Instruct
sambanova
In $0.6300 / 1M tokens
Out $1.8000 / 1M tokens
text
Output: unknown
Function callingTool choice
131.1K
Partial I/O overlap
Overall 42%
Missing text
Llama-3.1-Nemotron-Ultra-253B-v1
nebius
In $0.6000 / 1M tokens
Out $1.8000 / 1M tokens
text
Output: unknown
Function calling
128.0K
Partial I/O overlap
Overall 39%
Missing text