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minimax-m2.5

OpenRouter · chat model

minimax-m2.5 is listed here as a chat model from OpenRouter. This page shows simple API pricing, token limits, and capability flags so you can compare it with similar options.

Input
$0.3000 / 1M tokens
Output
$1.1000 / 1M tokens
Cached input
$0.1500 / 1M tokens
Context
65.5K
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
$0.3000 / 1M tokens
Output
$1.1000 / 1M tokens
Cached input
$0.1500 / 1M tokens
Embedding
$0.3000 / 1M tokens

Token limits

Context window
65.5K
Max input tokens
196.6K
Max output tokens
65.5K
Max tokens
65.5K

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
SWE-bench Verified 75.80% % resolved Base model: MiniMax M2.5 (MiniMax M2.5 (high reasoning)) 2026-05-31 Link
SWE-bench Verified 69.4 score Base model: MiniMax-M2 (MiniMax-M2) 2026-05-31 Link
Multi-SWE-bench 36.2 score Base model: MiniMax-M2 (MiniMax-M2) 2026-05-31 Link
SWE-bench Multilingual 56.5 score Base model: MiniMax-M2 (MiniMax-M2) 2026-05-31 Link
Terminal-Bench 46.3 score Base model: MiniMax-M2 (MiniMax-M2) 2026-05-31 Link
ArtifactsBench 66.8 score Base model: MiniMax-M2 (MiniMax-M2) 2026-05-31 Link
BrowseComp 44 score Base model: MiniMax-M2 (MiniMax-M2) 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
minimax-m2.5
OpenRouter
In $0.3000 / 1M tokens
Out $1.1000 / 1M tokens
text
Output: text
Function callingTool choicePrompt cachingReasoning
65.5K
Current model
Reference row

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

Model Cost Input shape Features Context Why it is close
minimax-m2.1
OpenRouter
In $0.2700 / 1M tokens
Out $1.2000 / 1M tokens
text
Output: text
Function callingTool choiceReasoning
64.0K
Same provider
Overall 88%
minimax-m2
OpenRouter
In $0.2550 / 1M tokens
Out $1.0200 / 1M tokens
text
Output: text
Function callingTool choicePrompt cachingReasoning
204.8K
Same provider
Overall 88%
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
Text covered
Overall 87%
glm-4.6
OpenRouter
In $0.4000 / 1M tokens
Out $1.7500 / 1M tokens
text
Output: text
Function callingTool choicePrompt cachingReasoning
131.0K
Same provider
Overall 86%
deepseek-chat-v3.1
OpenRouter
In $0.2000 / 1M tokens
Out $0.8000 / 1M tokens
text
Output: text
Function callingTool choicePrompt cachingReasoning
163.8K
Same provider
Overall 85%
glm-4.7
OpenRouter
In $0.4000 / 1M tokens
Out $1.5000 / 1M tokens
text
Output: text
Function callingTool choiceReasoning
64.0K
Same provider
Overall 84%
deepseek-v3.2
OpenRouter
In $0.2800 / 1M tokens
Out $0.4000 / 1M tokens
text
Output: text
Function callingTool choicePrompt cachingReasoning
163.8K
Same provider
Overall 83%
grok-code-fast
xai
In $0.2000 / 1M tokens
Out $1.5000 / 1M tokens
text
Output: text
Function callingTool choicePrompt cachingReasoning
256.0K
Text covered
Overall 83%
grok-code-fast-1
xai
In $0.2000 / 1M tokens
Out $1.5000 / 1M tokens
text
Output: text
Function callingTool choicePrompt cachingReasoning
256.0K
Text covered
Overall 83%
grok-code-fast-1-0825
xai
In $0.2000 / 1M tokens
Out $1.5000 / 1M tokens
text
Output: text
Function callingTool choicePrompt cachingReasoning
256.0K
Text covered
Overall 83%
deepseek-v3.2
azure_ai
In $0.5800 / 1M tokens
Out $1.6800 / 1M tokens
text
Output: text
Function callingTool choicePrompt cachingReasoning
163.8K
Text covered
Overall 83%
deepseek-v3.2-speciale
azure_ai
In $0.5800 / 1M tokens
Out $1.6800 / 1M tokens
text
Output: text
Function callingTool choicePrompt cachingReasoning
163.8K
Text covered
Overall 83%
deepseek-r1-0528
OpenRouter
In $0.5000 / 1M tokens
Out $2.1500 / 1M tokens
text
Output: text
Function callingTool choicePrompt cachingReasoning
8.2K
Same provider
Overall 78%
deepseek-r1
OpenRouter
In $0.5500 / 1M tokens
Out $2.1900 / 1M tokens
text
Output: text
Function callingTool choicePrompt cachingReasoning
8.2K
Same provider
Overall 77%
deepseek-v3-0324
novita
In $0.2700 / 1M tokens
Out $1.1200 / 1M tokens
text
Output: text
Function callingTool choice
163.8K
Text covered
Overall 72%
ernie-4.5-300b-a47b-paddle
novita
In $0.2800 / 1M tokens
Out $1.1000 / 1M tokens
text
Output: text
Tool choice
12.0K
Text covered
Overall 66%
qwen3-235b-a22b-instruct-2507
replicate
In $0.2640 / 1M tokens
Out $1.0600 / 1M tokens
text
Output: text
Function calling
N/A
Text covered
Overall 64%
deepseek-v3
DeepSeek
In $0.2700 / 1M tokens
Out $1.1000 / 1M tokens
text
Output: unknown
Function callingTool choicePrompt caching
8.2K
Partial I/O overlap
Overall 40%
Missing text
llama-4-maverick-17b-128e-instruct-maas
vertex_ai-llama_models
In $0.3500 / 1M tokens
Out $1.1500 / 1M tokens
text
Output: code, text
Function callingTool choice
1.0M
Partial I/O overlap
Overall 40%
Missing text
llama-4-maverick-17b-16e-instruct-maas
vertex_ai-llama_models
In $0.3500 / 1M tokens
Out $1.1500 / 1M tokens
text
Output: code, text
Function callingTool choice
1.0M
Partial I/O overlap
Overall 40%
Missing text