| Signal | Claude Haiku 4.5 | Delta | GLM 4.7 |
|---|---|---|---|
Capabilities | 100 | +33 | |
Benchmarks | 71 | -1 | |
Pricing | 5 | +3 | |
Context window size | 84 | 0 | |
Recency | 100 | -- | |
Output Capacity | 80 | 0 | |
| Overall Result | 2 wins | of 6 | 3 wins |
13
days higher
3
days
14
days higher
Anthropic
Zhipu AI
GLM 4.7 saves you $223.50/month
That's $2682.00/year compared to Claude Haiku 4.5 at your current usage level of 100K calls/month.
| Metric | Claude Haiku 4.5 | GLM 4.7 | Winner |
|---|---|---|---|
| Overall Score | 73 | 73 | Claude Haiku 4.5 |
| Rank | #52 | #53 | Claude Haiku 4.5 |
| Quality Rank | #52 | #53 | Claude Haiku 4.5 |
| Adoption Rank | #52 | #53 | Claude Haiku 4.5 |
| Parameters | -- | -- | -- |
| Context Window | 200K | 203K | GLM 4.7 |
| Pricing | $1.00/$5.00/M | $0.39/$1.75/M | -- |
| Signal Scores | |||
| Capabilities | 100 | 67 | Claude Haiku 4.5 |
| Benchmarks | 71 | 72 | GLM 4.7 |
| Pricing | 5 | 2 | Claude Haiku 4.5 |
| Context window size | 84 | 84 | GLM 4.7 |
| Recency | 100 | 100 | Claude Haiku 4.5 |
| Output Capacity | 80 | 80 | GLM 4.7 |
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%). Here's what the scores mean for these two models:
Scores 73/100 (rank #52), placing it in the top 82% of all 290 models tracked.
Scores 73/100 (rank #53), placing it in the top 82% of all 290 models tracked.
With only a 1-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.
GLM 4.7 offers 64% better value per quality point. At 1M tokens/day, you'd spend $32.10/month with GLM 4.7 vs $90.00/month with Claude Haiku 4.5 - a $57.90 monthly difference.
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.
Code generation & review
Higher benchmark score (0/100) indicates stronger performance on coding tasks like generating functions, debugging, and refactoring
Customer support chatbot
Faster response time (speed score 0/100) is critical for user-facing chat. GLM 4.7 also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (203K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($1.75/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (73/100) correlates with better nuance, coherence, and style in long-form content
Image understanding & OCR
Supports vision input - can analyze screenshots, diagrams, photos, and scanned documents directly
Claude Haiku 4.5 and GLM 4.7 are extremely close in overall performance (only 0.5 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.
Best for Quality
Claude Haiku 4.5
Marginally better benchmark scores; both are excellent
Best for Cost
GLM 4.7
64% lower pricing; better value at scale
Best for Reliability
Claude Haiku 4.5
Higher uptime and faster response speeds
Best for Prototyping
Claude Haiku 4.5
Stronger community support and better developer experience
Best for Production
Claude Haiku 4.5
Wider enterprise adoption and proven at scale
by Anthropic
| Capability | Claude Haiku 4.5 | GLM 4.7 |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Searchdiffers | ||
| Image Output |
Anthropic
Zhipu AI
GLM 4.7 saves you $5.00/month
That's 64% cheaper than Claude Haiku 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.
| Parameter | Claude Haiku 4.5 | GLM 4.7 |
|---|---|---|
| Context Window | 200K | 203K |
| Max Output Tokens | 64,000 | 65,535 |
| Open Source | No | Yes |
| Created | Oct 15, 2025 | Dec 22, 2025 |
Claude Haiku 4.5 scores 73/100 (rank #52) compared to GLM 4.7's 73/100 (rank #53), giving it a 1-point advantage. Claude Haiku 4.5 is the stronger overall choice, though GLM 4.7 may excel in specific areas like cost efficiency.
Claude Haiku 4.5 is ranked #52 and GLM 4.7 is ranked #53 out of 290+ AI models. Rankings use a composite score combining benchmark performance (90%) from MMLU, GPQA, HumanEval, SWE-bench, and 15+ standardized evaluations, with capabilities and context window as tiebreakers (10%). Scores update hourly.
GLM 4.7 is cheaper at $1.75/M output tokens vs Claude Haiku 4.5's $5.00/M output tokens - 2.9x more expensive. Input token pricing: Claude Haiku 4.5 at $1.00/M vs GLM 4.7 at $0.39/M.
GLM 4.7 has a larger context window of 202,752 tokens compared to Claude Haiku 4.5's 200,000 tokens. A larger context window means the model can process longer documents and conversations.