Model comparison
GLM-4.5-Air vs DeepSeek-R1
- Input
- $0.20
- Output
- $1.10
- Context
- 128K
- Released
- 2025-07-28
- Input
- $0.55 / 1M tokens (cache miss; $0.14 cache hit)
- Output
- $2.19 / 1M tokens
- Context
- 128K
- Released
- 2025-01-20
GLM-4.5-Air scores higher on 5 of the 6 benchmarks both models report (the other leads on 1); GLM-4.5-Air is cheaper on input tokens ($0.2 vs $0.6 per 1M, 2.8×).
Specs and pricing side by side
| Spec | GLM-4.5-Air | DeepSeek-R1 |
|---|---|---|
| Maker | Z.ai (Zhipu / GLM) | DeepSeek |
| Released | 2025-07-28 | 2025-01-20 |
| Context window | 128K | 128Ksame |
| Max output | 96K | 32,768 tokens (max generation length) |
| Input price | $0.20 | $0.55 / 1M tokens (cache miss; $0.14 cache hit) |
| Output price | $1.10 | $2.19 / 1M tokens |
| Parameters | 106B total · 12B active | 671B total / 37B active (Mixture-of-Experts) |
| License | MIT | MITsame |
| Weights | Open weights | Open weightssame |
| Modalities | Text | Textsame |
| Knowledge cutoff | Not disclosed | Not officially disclosed |
Benchmarks both models report
| Benchmark | GLM-4.5-Air | DeepSeek-R1 |
|---|---|---|
| MMLU-Pro | 81.4% | 84% |
| AIME 2024 | 89.4% | 79.8% |
| MATH-500 | 98.1% | 97.3% |
| GPQA Diamond | 71.72% | 71.5% |
| LiveCodeBench | 70.7% | 65.9% |
| SWE-bench Verified | 57.6% | 49.2% |
Scores are as published by each maker or its cited source; harness, reasoning effort and date can differ between rows, so treat small gaps as ties. Sources are listed on each model page.
Which one should you pick?
Pick GLM-4.5-Air if…
- You care about AIME 2024, MATH-500, GPQA Diamond (it scores higher on 5 shared benchmarks).
- Cost matters: input tokens cost 2.8× less ($0.2 vs $0.6 per 1M).
- Your use case is: agentic coding assistants and autonomous coding agents that call tools over long horizons.
Pick DeepSeek-R1 if…
- You care about MMLU-Pro (it scores higher on 1 shared benchmark).
- Your use case is: competition-style math and multi-step logical reasoning.
FAQ
Which is better, GLM-4.5-Air or DeepSeek-R1?
GLM-4.5-Air scores higher on 5 of the 6 benchmarks both models report (the other leads on 1); GLM-4.5-Air is cheaper on input tokens ($0.2 vs $0.6 per 1M, 2.8×). The better pick depends on whether you value benchmark scores, price per token, context length or openness for your workload.
How much cheaper is GLM-4.5-Air?
GLM-4.5-Air: $0.20 input, $1.10 output. DeepSeek-R1: $0.55 / 1M tokens (cache miss; $0.14 cache hit) input, $2.19 / 1M tokens output (list API prices as published by each maker).
What are the context windows of GLM-4.5-Air and DeepSeek-R1?
GLM-4.5-Air offers 128K with up to 96K output; DeepSeek-R1 offers 128K with up to 32,768 tokens (max generation length) output.
Is GLM-4.5-Air newer than DeepSeek-R1?
GLM-4.5-Air was released 2025-07-28; DeepSeek-R1 was released 2025-01-20.