| Signal | GPT-4o Audio | Delta | GLM 4.5 Air |
|---|---|---|---|
Capabilities | 50 | -- | |
Benchmarks | 74 | +2 | |
Pricing | 90 | -9 | |
Context window size | 81 | 0 | |
Recency | 84 | +4 | |
Output Capacity | 70 | -13 | |
| Overall Result | 2 wins | of 6 | 3 wins |
Score History
70.4
current score
GLM 4.5 Air
right now
70.7
current score
OpenAI
Zhipu AI
GLM 4.5 Air saves you $694.50/month
That's $8334.00/year compared to GPT-4o Audio at your current usage level of 100K calls/month.
| Metric | GPT-4o Audio | GLM 4.5 Air | Winner |
|---|---|---|---|
| Overall Score | 70 | 71 | GLM 4.5 Air |
| Rank | #96 | #94 | GLM 4.5 Air |
| Quality Rank | #96 | #94 | GLM 4.5 Air |
| Adoption Rank | #96 | #94 | GLM 4.5 Air |
| Parameters | -- | -- | -- |
| Context Window | 128K | 131K | GLM 4.5 Air |
| Pricing | $2.50/$10.00/M | $0.13/$0.85/M | -- |
| Signal Scores | |||
| Capabilities | 50 | 50 | GPT-4o Audio |
| Benchmarks | 74 | 72 | GPT-4o Audio |
| Pricing | 90 | 99 | GLM 4.5 Air |
| Context window size | 81 | 81 | GLM 4.5 Air |
| Recency | 84 | 80 | GPT-4o Audio |
| Output Capacity | 70 | 83 | GLM 4.5 Air |
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 70/100 (rank #96), placing it in the top 67% of all 290 models tracked.
Scores 71/100 (rank #94), placing it in the top 68% 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 4.5 Air offers 92% better value per quality point. At 1M tokens/day, you'd spend $14.70/month with GLM 4.5 Air vs $187.50/month with GPT-4o Audio - a $172.80 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 4.5 Air 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 ($0.85/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (71/100) correlates with better nuance, coherence, and style in long-form content
GPT-4o Audio and GLM 4.5 Air are extremely close in overall performance (only 0.29999999999999716 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.
Best for Quality
GPT-4o Audio
Marginally better benchmark scores; both are excellent
Best for Cost
GLM 4.5 Air
92% lower pricing; better value at scale
Best for Reliability
GPT-4o Audio
Higher uptime and faster response speeds
Best for Prototyping
GPT-4o Audio
Stronger community support and better developer experience
Best for Production
GPT-4o Audio
Wider enterprise adoption and proven at scale
by OpenAI
| Capability | GPT-4o Audio | GLM 4.5 Air |
|---|---|---|
| Vision (Image Input) | ||
| Function Calling | ||
| Streaming | ||
| JSON Modediffers | ||
| Reasoningdiffers | ||
| Web Search | ||
| Image Output |
OpenAI
Zhipu AI
GLM 4.5 Air saves you $15.25/month
That's 92% cheaper than GPT-4o Audio 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-4o Audio | GLM 4.5 Air |
|---|---|---|
| Context Window | 128K | 131K |
| Max Output Tokens | 16,384 | 98,304 |
| Open Source | No | Yes |
| Created | Aug 15, 2025 | Jul 25, 2025 |