| Signal | GPT-5.3-Codex | Delta | GLM 5 |
|---|---|---|---|
Capabilities | 100 | +33 | |
Pricing | 14 | +12 | |
Context window size | 89 | +11 | |
Recency | 100 | -- | |
Output Capacity | 85 | 0 | |
| Overall Result | 3 wins | of 5 | 1 wins |
24
days higher
3
days
3
days higher
OpenAI
Zhipu AI
GLM 5 saves you $688.00/month
That's $8256.00/year compared to GPT-5.3-Codex at your current usage level of 100K calls/month.
| Metric | GPT-5.3-Codex | GLM 5 | Winner |
|---|---|---|---|
| Overall Score | 85 | 82 | GPT-5.3-Codex |
| Rank | #29 | #72 | GPT-5.3-Codex |
| Quality Rank | #29 | #72 | GPT-5.3-Codex |
| Adoption Rank | #29 | #72 | GPT-5.3-Codex |
| Parameters | -- | -- | -- |
| Context Window | 400K | 80K | GPT-5.3-Codex |
| Pricing | $1.75/$14.00/M | $0.72/$2.30/M | -- |
| Signal Scores | |||
| Capabilities | 100 | 67 | GPT-5.3-Codex |
| Pricing | 14 | 2 | GPT-5.3-Codex |
| Context window size | 89 | 78 | GPT-5.3-Codex |
| Recency | 100 | 100 | GPT-5.3-Codex |
| Output Capacity | 85 | 85 | GLM 5 |
Our composite score (0–100) combines six weighted signals: benchmark performance (25%), pricing efficiency (25%), context window size (15%), model recency (15%), output capacity (10%), and capability versatility (10%). Here's what the scores mean for these two models:
Scores 85/100 (rank #29), placing it in the top 90% of all 290 models tracked.
Scores 82/100 (rank #72), placing it in the top 76% of all 290 models tracked.
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.
GLM 5 offers 81% better value per quality point. At 1M tokens/day, you'd spend $45.30/month with GLM 5 vs $236.25/month with GPT-5.3-Codex - a $190.95 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 5 also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (400K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($2.30/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (85/100) 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
GPT-5.3-Codex has a moderate advantage with a 3.299999999999997-point lead in composite score. It wins on more signal dimensions, but GLM 5 has specific strengths that could make it the better choice for certain workflows.
Best for Quality
GPT-5.3-Codex
Marginally better benchmark scores; both are excellent
Best for Cost
GLM 5
81% lower pricing; better value at scale
Best for Reliability
GPT-5.3-Codex
Higher uptime and faster response speeds
Best for Prototyping
GPT-5.3-Codex
Stronger community support and better developer experience
Best for Production
GPT-5.3-Codex
Wider enterprise adoption and proven at scale
by OpenAI
| Capability | GPT-5.3-Codex | GLM 5 |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Searchdiffers | ||
| Image Output |
OpenAI
Zhipu AI
GLM 5 saves you $15.89/month
That's 80% cheaper than GPT-5.3-Codex 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 | GPT-5.3-Codex | GLM 5 |
|---|---|---|
| Context Window | 400K | 80K |
| Max Output Tokens | 128,000 | 131,072 |
| Open Source | No | Yes |
| Created | Feb 24, 2026 | Feb 11, 2026 |
GPT-5.3-Codex scores 85/100 (rank #29) compared to GLM 5's 82/100 (rank #72), giving it a 3-point advantage. GPT-5.3-Codex is the stronger overall choice, though GLM 5 may excel in specific areas like cost efficiency.
GPT-5.3-Codex is ranked #29 and GLM 5 is ranked #72 out of 290+ AI models. Rankings use a composite score combining benchmark performance (25%), pricing (25%), context window (15%), recency (15%), output capacity (10%), and versatility (10%). Scores update hourly.
GLM 5 is cheaper at $2.30/M output tokens vs GPT-5.3-Codex's $14.00/M output tokens - 6.1x more expensive. Input token pricing: GPT-5.3-Codex at $1.75/M vs GLM 5 at $0.72/M.
GPT-5.3-Codex has a larger context window of 400,000 tokens compared to GLM 5's 80,000 tokens. A larger context window means the model can process longer documents and conversations.