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Claude Opus 4.1 (batch) vs GLM 5.1

vs
GLM 5.1

Zhipu AI

78#107
Signal-by-Signal Comparison
SignalClaude Opus 4.1 (batch)DeltaGLM 5.1
Capabilities
100
+33
67
Benchmarks
73
-2
76
Pricing
63
-34
97
Context window size
84
0
84
Recency
60
-40
100
Output Capacity
72
-10
82
Overall Result
1 wins
of 6
5 wins
GLM 5.1 wins 5 of 6 signals

Score History

Score History (23 data points)
Claude Opus 4.1 (batch)GLM 5.1
Claude Opus 4.1 (batch)

75.2

current score

Leader

GLM 5.1

right now

GLM 5.1

78

current score

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

Claude Opus 4.1 (batch)

Anthropic

Per request$0.026250
Daily$87.50
Monthly$2625.00
Annual$31500.00

GLM 5.1

Zhipu AI

Best Value
Per request$0.002484
Daily$8.28
Monthly$248.40
Annual$2980.80

GLM 5.1 saves you $2376.60/month

That's $28519.20/year compared to Claude Opus 4.1 (batch) at your current usage level of 100K calls/month.

91% cheaper
Choose GLM 5.1 for cost optimization

Claude Opus 4.1 (batch) pricing:
Input:$7.50/M tokens
Output:$37.50/M tokens
GLM 5.1 pricing:
Input:$0.97/M tokens
Output:$3.04/M tokens
Claude Opus 4.1 (batch)

Anthropic

75

Composite Score

Winner
GLM 5.1

Zhipu AI

78

Composite Score

Signal-by-Signal Comparison
MetricClaude Opus 4.1 (batch)GLM 5.1Winner
Overall Score
75
78
GLM 5.1
Rank#125#107
GLM 5.1
Quality Rank#125#107
GLM 5.1
Adoption Rank#125#107
GLM 5.1
Parameters------
Context Window200K205K
GLM 5.1
Pricing$7.50/$37.50/M$0.97/$3.04/M--
Signal Scores
Capabilities
100
67
Claude Opus 4.1 (batch)
Benchmarks
73
76
GLM 5.1
Pricing
63
97
GLM 5.1
Context window size
84
84
GLM 5.1
Recency
60
100
GLM 5.1
Output Capacity
72
82
GLM 5.1
Benchmark Head-to-Head(1 benchmarks)
Claude Opus: 0GLM 5.1: 1
Claude Opus
GLM 5.1
Normalized 0-100%
Arena Elo
14501466
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.

Claude Opus 4.1 (batch)Strong Performer

Scores 75/100 (rank #125), placing it in the top 57% of all 290 models tracked.

Raw Quality0/100
Cost Efficiency0/100
Speed0/100
GLM 5.1Strong Performer

Scores 78/100 (rank #107), placing it in the top 63% of all 290 models tracked.

Raw Quality0/100
Cost Efficiency0/100
Speed0/100

With only a 3-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 Claude Opus 4.1 (batch) when you need:

  • Multimodal workflows that require image understanding
  • Step-by-step reasoning and chain-of-thought problem solving

Choose GLM 5.1 when you need:

  • High-volume production workloads where API costs must be minimized
  • Step-by-step reasoning and chain-of-thought problem solving
  • Self-hosted deployments where you need full control over the model
Cost-Performance Analysis
Claude Opus 4.1 (batch)
Input cost$7.50/M tokens
Output cost$37.50/M tokens
Cost per quality point$0.598
Est. monthly (1M tokens/day)$675.00
GLM 5.1Best Value
Input cost$0.97/M tokens
Output cost$3.04/M tokens
Cost per quality point$0.051
Est. monthly (1M tokens/day)$60.03

GLM 5.1 offers 91% better value per quality point. At 1M tokens/day, you'd spend $60.03/month with GLM 5.1 vs $675.00/month with Claude Opus 4.1 (batch) - a $614.97 monthly difference.

Latency & Speed
Claude Opus 4.1 (batch)Faster
Speed score0/100
GLM 5.1
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

Claude Opus 4.1 (batch)

Customer support chatbot

Suitable for user-facing chat with competitive response times. GLM 5.1 also offers lower per-token costs for high-volume support

Claude Opus 4.1 (batch)

Long document analysis

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

GLM 5.1

Batch data extraction

Lower output pricing ($3.04/M) reduces costs when processing thousands of records daily

GLM 5.1

Creative writing & content

Higher overall composite score (78/100) correlates with better nuance, coherence, and style in long-form content

GLM 5.1

Image understanding & OCR

Supports vision input - can analyze screenshots, diagrams, photos, and scanned documents directly

Claude Opus 4.1 (batch)
Which Should You Choose?
Our recommendation:
GLM 5.1

Claude Opus 4.1 (batch) and GLM 5.1 are extremely close in overall performance (only 2.799999999999997 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.

by Anthropic

  • 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
GLM 5.1
Recommended

by Zhipu AI

  • Choose for Cost - 91% lower pricing; better value at scale
Capability Comparison
CapabilityClaude Opus 4.1 (batch)GLM 5.1
Vision (Image Input)differs
Function Calling
Streaming
JSON Mode
Reasoning
Web Searchdiffers
Image Output
Monthly Cost Calculator
1,000tokens (600 in / 400 out)
100requests/day (3,000/month)

Claude Opus 4.1 (batch)

Anthropic

$58.50
estimated monthly cost

GLM 5.1

Zhipu AI

Best Value
$5.38
estimated monthly cost

GLM 5.1 saves you $53.12/month

That's 91% cheaper than Claude Opus 4.1 (batch) 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
ParameterClaude Opus 4.1 (batch)GLM 5.1
Context Window200K205K
Max Output Tokens32,000128,000
Open SourceNoYes
CreatedAug 5, 2025Apr 7, 2026
Last updated: 53m ago

相关对比

Claude Opus 4.1 (batch) vs GLM 5.1 (2026) | LM Market Cap