| Signal | o1-pro | Delta | GLM 4.7 |
|---|---|---|---|
Capabilities | 67 | -- | |
Benchmarks | 77 | +4 | |
Pricing | 5 | -93 | |
Context window size | 84 | 0 | |
Recency | 64 | -36 | |
Output Capacity | 83 | +3 | |
| Overall Result | 2 wins | of 6 | 3 wins |
Score History
72.7
current score
Tied
right now
72.7
current score
OpenAI
Zhipu AI
GLM 4.7 saves you $44873.50/month
That's $538482.00/year compared to o1-pro at your current usage level of 100K calls/month.
| Metric | o1-pro | GLM 4.7 | Winner |
|---|---|---|---|
| Overall Score | 73 | 73 | -- |
| Rank | #42 | #41 | GLM 4.7 |
| Quality Rank | #42 | #41 | GLM 4.7 |
| Adoption Rank | #42 | #41 | GLM 4.7 |
| Parameters | -- | -- | -- |
| Context Window | 200K | 203K | GLM 4.7 |
| Pricing | $150.00/$600.00/M | $0.39/$1.75/M | -- |
| Signal Scores | |||
| Capabilities | 67 | 67 | o1-pro |
| Benchmarks | 77 | 72 | o1-pro |
| Pricing | 5 | 98 | GLM 4.7 |
| Context window size | 84 | 84 | GLM 4.7 |
| Recency | 64 | 100 | GLM 4.7 |
| Output Capacity | 83 | 80 | o1-pro |
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.
Scores 73/100 (rank #42), placing it in the top 86% of all 290 models tracked.
Scores 73/100 (rank #41), placing it in the top 86% of all 290 models tracked.
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.
GLM 4.7 offers 100% better value per quality point. At 1M tokens/day, you'd spend $32.10/month with GLM 4.7 vs $11250.00/month with o1-pro - a $11217.90 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
o1-pro and GLM 4.7 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.
Best for Quality
o1-pro
Marginally better benchmark scores; both are excellent
Best for Cost
GLM 4.7
100% lower pricing; better value at scale
Best for Reliability
o1-pro
Higher uptime and faster response speeds
Best for Prototyping
o1-pro
Stronger community support and better developer experience
Best for Production
o1-pro
Wider enterprise adoption and proven at scale
by OpenAI
| Capability | o1-pro | GLM 4.7 |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Callingdiffers | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Search | ||
| Image Output |
OpenAI
Zhipu AI
GLM 4.7 saves you $987.20/month
That's 100% cheaper than o1-pro 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 | o1-pro | GLM 4.7 |
|---|---|---|
| Context Window | 200K | 203K |
| Max Output Tokens | 100,000 | 65,535 |
| Open Source | No | Yes |
| Created | Mar 19, 2025 | Dec 22, 2025 |
Both o1-pro and GLM 4.7 score 73/100, making them extremely close competitors. Choose based on pricing, provider ecosystem, or specific capability requirements.
o1-pro is ranked #42 and GLM 4.7 is ranked #41 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 o1-pro's $600.00/M output tokens - 342.9x more expensive. Input token pricing: o1-pro at $150.00/M vs GLM 4.7 at $0.39/M.
GLM 4.7 has a larger context window of 202,752 tokens compared to o1-pro's 200,000 tokens. A larger context window means the model can process longer documents and conversations.