| Signal | GPT-4 (older v0314) | Delta | GLM 4.6V |
|---|---|---|---|
Capabilities | 50 | -17 | |
Benchmarks | 66 | +2 | |
Pricing | 40 | -59 | |
Context window size | 62 | -19 | |
Recency | 0 | -100 | |
Output Capacity | 60 | -13 | |
| Overall Result | 1 wins | of 6 | 5 wins |
Score History
64.8
current score
Tied
right now
64.8
current score
OpenAI
Zhipu AI
GLM 4.6V saves you $5925.00/month
That's $71100.00/year compared to GPT-4 (older v0314) at your current usage level of 100K calls/month.
| Metric | GPT-4 (older v0314) | GLM 4.6V | Winner |
|---|---|---|---|
| Overall Score | 65 | 65 | -- |
| Rank | #131 | #130 | GLM 4.6V |
| Quality Rank | #131 | #130 | GLM 4.6V |
| Adoption Rank | #131 | #130 | GLM 4.6V |
| Parameters | -- | -- | -- |
| Context Window | 8K | 131K | GLM 4.6V |
| Pricing | $30.00/$60.00/M | $0.30/$0.90/M | -- |
| Signal Scores | |||
| Capabilities | 50 | 67 | GLM 4.6V |
| Benchmarks | 66 | 64 | GPT-4 (older v0314) |
| Pricing | 40 | 99 | GLM 4.6V |
| Context window size | 62 | 81 | GLM 4.6V |
| Recency | 0 | 100 | GLM 4.6V |
| Output Capacity | 60 | 73 | GLM 4.6V |
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 65/100 (rank #131), placing it in the top 55% of all 290 models tracked.
Scores 65/100 (rank #130), placing it in the top 56% 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 4.6V offers 99% better value per quality point. At 1M tokens/day, you'd spend $18.00/month with GLM 4.6V vs $1350.00/month with GPT-4 (older v0314) - a $1332.00 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
Based on overall model capabilities and architecture for coding tasks like generating functions, debugging, and refactoring
Customer support chatbot
Suitable for user-facing chat with competitive response times. GLM 4.6V also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (131K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($0.90/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (65/100) 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-4 (older v0314) and GLM 4.6V 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
GPT-4 (older v0314)
Marginally better benchmark scores; both are excellent
Best for Cost
GLM 4.6V
99% lower pricing; better value at scale
Best for Reliability
GPT-4 (older v0314)
Higher uptime and faster response speeds
Best for Prototyping
GPT-4 (older v0314)
Stronger community support and better developer experience
Best for Production
GPT-4 (older v0314)
Wider enterprise adoption and proven at scale
by OpenAI
| Capability | GPT-4 (older v0314) | GLM 4.6V |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Calling | ||
| Streaming | ||
| JSON Modediffers | ||
| Reasoningdiffers | ||
| Web Search | ||
| Image Output |
OpenAI
Zhipu AI
GLM 4.6V saves you $124.38/month
That's 99% cheaper than GPT-4 (older v0314) 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-4 (older v0314) | GLM 4.6V |
|---|---|---|
| Context Window | 8K | 131K |
| Max Output Tokens | 4,096 | 24,000 |
| Open Source | No | Yes |
| Created | May 28, 2023 | Dec 8, 2025 |