| Signal | GPT-5.3-Codex | Delta | GLM 4.7 Flash |
|---|---|---|---|
Capabilities | 100 | +33 | |
Pricing | 14 | +14 | |
Context window size | 89 | +5 | |
Recency | 100 | -- | |
Output Capacity | 85 | +65 | |
| Overall Result | 4 wins | of 5 | 0 wins |
30
days higher
0
days
0
days higher
OpenAI
Zhipu AI
GLM 4.7 Flash saves you $849.00/month
That's $10188.00/year compared to GPT-5.3-Codex at your current usage level of 100K calls/month.
| Metric | GPT-5.3-Codex | GLM 4.7 Flash | Winner |
|---|---|---|---|
| Overall Score | 85 | 73 | GPT-5.3-Codex |
| Rank | #29 | #134 | GPT-5.3-Codex |
| Quality Rank | #29 | #134 | GPT-5.3-Codex |
| Adoption Rank | #29 | #134 | GPT-5.3-Codex |
| Parameters | -- | -- | -- |
| Context Window | 400K | 203K | GPT-5.3-Codex |
| Pricing | $1.75/$14.00/M | $0.06/$0.40/M | -- |
| Signal Scores | |||
| Capabilities | 100 | 67 | GPT-5.3-Codex |
| Pricing | 14 | 0 | GPT-5.3-Codex |
| Context window size | 89 | 84 | GPT-5.3-Codex |
| Recency | 100 | 100 | GPT-5.3-Codex |
| Output Capacity | 85 | 20 | GPT-5.3-Codex |
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 73/100 (rank #134), placing it in the top 54% of all 290 models tracked.
GPT-5.3-Codex has a 12-point advantage, which typically translates to noticeably better performance on complex reasoning, code generation, and multi-step tasks.
GLM 4.7 Flash offers 97% better value per quality point. At 1M tokens/day, you'd spend $6.90/month with GLM 4.7 Flash vs $236.25/month with GPT-5.3-Codex - a $229.35 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 Flash 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 ($0.40/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 clearly outperforms GLM 4.7 Flash with a significant 11.799999999999997-point lead. For most general use cases, GPT-5.3-Codex is the stronger choice. However, GLM 4.7 Flash may still excel in niche scenarios.
Best for Quality
GPT-5.3-Codex
Marginally better benchmark scores; both are excellent
Best for Cost
GLM 4.7 Flash
97% 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 4.7 Flash |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Searchdiffers | ||
| Image Output |
OpenAI
Zhipu AI
GLM 4.7 Flash saves you $19.36/month
That's 97% 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 4.7 Flash |
|---|---|---|
| Context Window | 400K | 203K |
| Max Output Tokens | 128,000 | -- |
| Open Source | No | Yes |
| Created | Feb 24, 2026 | Jan 19, 2026 |
GPT-5.3-Codex scores 85/100 (rank #29) compared to GLM 4.7 Flash's 73/100 (rank #134), giving it a 12-point advantage. GPT-5.3-Codex is the stronger overall choice, though GLM 4.7 Flash may excel in specific areas like cost efficiency.
GPT-5.3-Codex is ranked #29 and GLM 4.7 Flash is ranked #134 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 4.7 Flash is cheaper at $0.40/M output tokens vs GPT-5.3-Codex's $14.00/M output tokens - 35.0x more expensive. Input token pricing: GPT-5.3-Codex at $1.75/M vs GLM 4.7 Flash at $0.06/M.
GPT-5.3-Codex has a larger context window of 400,000 tokens compared to GLM 4.7 Flash's 202,752 tokens. A larger context window means the model can process longer documents and conversations.