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GLM 4.5 vs GLM 4.6

GLM 4.5

Zhipu AI

67#141
vs
GLM 4.6

Zhipu AI

67#140
Signal-by-Signal Comparison
SignalGLM 4.5DeltaGLM 4.6
Capabilities
67
--
67
Benchmarks
68
+68
0
Pricing
98
0
98
Context window size
81
-3
84
Recency
48
-12
60
Output Capacity
80
-2
82
Overall Result
1 wins
of 6
4 wins
GLM 4.6 wins 4 of 6 signals

Score History

Score History (33 data points)
GLM 4.5GLM 4.6
GLM 4.5

67.1

current score

Leader

Tied

right now

GLM 4.6

67.1

current score

LMMarketCap.com
Interactive Price Comparison
100Kcalls/month
1,000tokens (~1,333 chars)
500tokens (~667 chars)

GLM 4.5

Zhipu AI

Per request$0.001700
Daily$5.67
Monthly$170.00
Annual$2040.00

GLM 4.6

Zhipu AI

Best Value
Per request$0.001500
Daily$5.00
Monthly$150.00
Annual$1800.00

GLM 4.6 saves you $20.00/month

That's $240.00/year compared to GLM 4.5 at your current usage level of 100K calls/month.

12% cheaper
Choose GLM 4.6 for cost optimization

GLM 4.5 pricing:
Input:$0.60/M tokens
Output:$2.20/M tokens
GLM 4.6 pricing:
Input:$0.50/M tokens
Output:$2.00/M tokens
Tie
GLM 4.5

Zhipu AI

67

Composite Score

Tie
GLM 4.6

Zhipu AI

67

Composite Score

Signal-by-Signal Comparison
MetricGLM 4.5GLM 4.6Winner
Overall Score
67
67
--
Rank#141#140
GLM 4.6
Quality Rank#141#140
GLM 4.6
Adoption Rank#141#140
GLM 4.6
Parameters------
Context Window131K205K
GLM 4.6
Pricing$0.60/$2.20/M$0.50/$2.00/M--
Signal Scores
Capabilities
67
67
GLM 4.5
Benchmarks
68
--
GLM 4.5
Pricing
98
98
GLM 4.6
Context window size
81
84
GLM 4.6
Recency
48
60
GLM 4.6
Output Capacity
80
82
GLM 4.6
Benchmark Head-to-Head(2 benchmarks)
GLM 4.5: 0GLM 4.6: 0
GLM 4.5
GLM 4.6
Normalized 0-100%
MMLU-Pro
84.6%-
HLE
-8.32%
Benchmark Interpretation

Our score (0-100) is driven by benchmark performance (90%) from Arena Elo ratings, MMLU, GPQA, HumanEval, SWE-bench, and 15+ standardized evaluations. Capabilities and context window serve as tiebreakers (10%). Learn more about our methodology.

GLM 4.5Competitive

Scores 67/100 (rank #141), placing it in the top 52% of all 290 models tracked.

Raw Quality0/100
Cost Efficiency0/100
Speed0/100
GLM 4.6Competitive

Scores 67/100 (rank #140), placing it in the top 52% of all 290 models tracked.

Raw Quality0/100
Cost Efficiency0/100
Speed0/100

With only a 0-point gap, these models are in the same performance tier. The practical difference in output quality is minimal - your choice should depend on pricing, latency requirements, and specific feature needs.

When to Use Each Model

Choose GLM 4.5 when you need:

  • Step-by-step reasoning and chain-of-thought problem solving
  • Self-hosted deployments where you need full control over the model

Choose GLM 4.6 when you need:

  • Processing long documents or large codebases (205K token context)
  • Step-by-step reasoning and chain-of-thought problem solving
  • Self-hosted deployments where you need full control over the model
Cost-Performance Analysis
GLM 4.5
Input cost$0.60/M tokens
Output cost$2.20/M tokens
Cost per quality point$0.042
Est. monthly (1M tokens/day)$42.00
GLM 4.6Best Value
Input cost$0.50/M tokens
Output cost$2.00/M tokens
Cost per quality point$0.037
Est. monthly (1M tokens/day)$37.50

GLM 4.6 offers 11% better value per quality point. At 1M tokens/day, you'd spend $37.50/month with GLM 4.6 vs $42.00/month with GLM 4.5 - a $4.50 monthly difference.

Latency & Speed
GLM 4.5Faster
Speed score0/100
GLM 4.6
Speed score0/100

Both models have comparable response speeds. For most applications, the latency difference is negligible.

When latency matters most: Interactive chatbots, IDE code completion, real-time translation, and user-facing applications where response time directly impacts experience. For batch processing, background summarization, or offline analysis, latency is less critical.

Example Use Cases

Code generation & review

Based on overall model capabilities and architecture for coding tasks like generating functions, debugging, and refactoring

GLM 4.5

Customer support chatbot

Suitable for user-facing chat with competitive response times. GLM 4.6 also offers lower per-token costs for high-volume support

GLM 4.5

Long document analysis

Larger context window (205K tokens) can process longer documents, contracts, and research papers in a single pass

GLM 4.6

Batch data extraction

Lower output pricing ($2.00/M) reduces costs when processing thousands of records daily

GLM 4.6

Creative writing & content

Higher overall composite score (67/100) correlates with better nuance, coherence, and style in long-form content

GLM 4.5
Which Should You Choose?
Our recommendation:
GLM 4.5

GLM 4.5 and GLM 4.6 are extremely close in overall performance (only 0 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.

GLM 4.5
Recommended

by Zhipu AI

  • Choose for Quality - Marginally better benchmark scores; both are excellent
  • Choose for Reliability - Higher uptime and faster response speeds
  • Choose for Prototyping - Stronger community support and better developer experience
  • Choose for Production - Wider enterprise adoption and proven at scale

by Zhipu AI

  • Choose for Cost - 11% lower pricing; better value at scale
Capability Comparison
CapabilityGLM 4.5GLM 4.6
Vision (Image Input)
Function Calling
Streaming
JSON Mode
Reasoning
Web Search
Image Output
Monthly Cost Calculator
1,000tokens (600 in / 400 out)
100requests/day (3,000/month)

GLM 4.5

Zhipu AI

$3.72
estimated monthly cost

GLM 4.6

Zhipu AI

Best Value
$3.30
estimated monthly cost

GLM 4.6 saves you $0.4200/month

That's 11% cheaper than GLM 4.5 at 1,000 tokens/request and 100 requests/day.

Assumes 60% input / 40% output token ratio per request. Actual costs may vary based on your usage pattern.

Parameters & Context
ParameterGLM 4.5GLM 4.6
Context Window131K205K
Max Output Tokens98,304131,072
Open SourceYesYes
CreatedJul 25, 2025Sep 30, 2025
Last updated: 11m ago

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GLM 4.5 vs GLM 4.6 (2026) | LM Market Cap