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glm-4.7

OpenRouter · chat model

glm-4.7 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
$0.4000 / 1M tokens
Output
$1.5000 / 1M tokens
Cached input
N/A
0 in raw data; semantics unverified
Context
64.0K

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
$0.4000 / 1M tokens
Output
$1.5000 / 1M tokens
Cached input
N/A
0 in raw data; semantics unverified
Cache write
N/A
0 in raw data; semantics unverified
Embedding
$0.4000 / 1M tokens

Token limits

Context window
64.0K
Max input tokens
202.8K
Max output tokens
64.0K
Max tokens
64.0K

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 74.7 score Base model: GLM (GLM-4-9B) 2026-05-31 Link
C-Eval 77.1 score Base model: GLM (GLM-4-9B) 2026-05-31 Link
GPQA 34.3 score Base model: GLM (GLM-4-9B) 2026-05-31 Link
GSM8K 84.0 score Base model: GLM (GLM-4-9B) 2026-05-31 Link
MATH 30.4 score Base model: GLM (GLM-4-9B) 2026-05-31 Link
HumanEval 70.1 score Base model: GLM (GLM-4-9B) 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
glm-4.7
OpenRouter
In $0.4000 / 1M tokens
Out $1.5000 / 1M tokens
text
Output: text
VisionFunction callingTool choiceReasoning
64.0K
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
VisionFunction callingTool choiceReasoning
64.0K
Same provider
Overall 95%
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 88%
deepseek.v3-v1:0
bedrock_converse
In $0.5800 / 1M tokens
Out $1.6800 / 1M tokens
text
Output: text
Function callingTool choiceReasoning
81.9K
Text covered
Overall 86%
qwen3-coder
vercel_ai_gateway
In $0.4000 / 1M tokens
Out $1.6000 / 1M tokens
text
Output: text
Function callingTool choice
66.5K
Text covered
Overall 86%
minimax-m2.5
OpenRouter
In $0.3000 / 1M tokens
Out $1.1000 / 1M tokens
text
Output: text
Function callingTool choiceReasoning
65.5K
Same provider
Overall 84%
magistral-small-2506
Mistral
In $0.5000 / 1M tokens
Out $1.5000 / 1M tokens
text
Output: text
Function callingTool choiceReasoning
40.0K
Text covered
Overall 83%
qwen3.5-122b-a10b
OpenRouter
In $0.4000 / 1M tokens
Out $2.0000 / 1M tokens
text imagevideo
Output: text
VisionFunction callingTool choiceReasoning
65.5K
Same provider
Overall 81%
glm-4.6
OpenRouter
In $0.4000 / 1M tokens
Out $1.7500 / 1M tokens
text
Output: text
Function callingTool choiceReasoning
131.0K
Same provider
Overall 81%
qwen3-coder-plus
OpenRouter
In $1.0000 / 1M tokens
Out $5.0000 / 1M tokens
text
Output: text
Function callingTool choiceReasoning
65.5K
Same provider
Overall 80%
qwen3.5-plus-02-15
OpenRouter
In $0.4000 / 1M tokens
Out $2.4000 / 1M tokens
text imagevideo
Output: text
VisionFunction callingTool choiceReasoning
65.5K
Same provider
Overall 80%
qwen3.6-plus
OpenRouter
In $0.3250 / 1M tokens
Out $1.9500 / 1M tokens
text imagevideo
Output: text
VisionFunction callingTool choiceReasoning
65.5K
Same provider
Overall 79%
qwen3.5-35b-a3b
OpenRouter
In $0.2500 / 1M tokens
Out $2.0000 / 1M tokens
text imagevideo
Output: text
VisionFunction callingTool choiceReasoning
65.5K
Same provider
Overall 78%
qwen3.5-27b
OpenRouter
In $0.3000 / 1M tokens
Out $2.4000 / 1M tokens
text imagevideo
Output: text
VisionFunction callingTool choiceReasoning
65.5K
Same provider
Overall 77%
glm-4.7-flash
OpenRouter
In $0.0700 / 1M tokens
Out $0.4000 / 1M tokens
text
Output: text
VisionFunction callingTool choiceReasoning
32.0K
Same provider
Overall 77%
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 77%
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 77%
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 77%
minimax.minimax-m2.5
Bedrock
In $0.3600 / 1M tokens
Out $1.4400 / 1M tokens
text
Output: text
Function callingTool choiceReasoning
8.2K
Text covered
Overall 76%
minimax.minimax-m2.5
Bedrock
In $0.3600 / 1M tokens
Out $1.4400 / 1M tokens
text
Output: text
Function callingTool choiceReasoning
8.2K
Text covered
Overall 76%
minimax.minimax-m2.5
Bedrock
In $0.3600 / 1M tokens
Out $1.4400 / 1M tokens
text
Output: text
Function callingTool choiceReasoning
8.2K
Text covered
Overall 76%
minimax.minimax-m2.1
Bedrock
In $0.3600 / 1M tokens
Out $1.4400 / 1M tokens
text
Output: text
Function callingTool choice
8.2K
Text covered
Overall 71%
minimax.minimax-m2.1
Bedrock
In $0.3600 / 1M tokens
Out $1.4400 / 1M tokens
text
Output: text
Function callingTool choice
8.2K
Text covered
Overall 71%
minimax.minimax-m2.1
Bedrock
In $0.3600 / 1M tokens
Out $1.4400 / 1M tokens
text
Output: text
Function callingTool choice
8.2K
Text covered
Overall 71%
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 66%