GLM-5.1 vs DeepSeek-R1
GLM-5.1 comes out ahead, 57 to 51 on our weighted score, though DeepSeek-R1 is 45% cheaper per token.
- Our pick
Z.ai (Zhipu)GLM-5.1
57/100- ECI149.9
- Price$1.40 / $4.40
- Context200K
DeepSeekDeepSeek-R1
51/100- ECI139.0
- Price$0.70 / $2.60
- Context128K
Add a model
Make it a three-way comparison.
GLM-5.1 is our pick
GLM-5.1 is the better all-round choice, scoring 57/100 against DeepSeek-R1 (51). It leads on capability, inputs & features and context window. DeepSeek-R1 wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityGLM-5.1Capabilities Index (ECI): GLM-5.1 149.9 · DeepSeek-R1 139.0
- Lowest priceDeepSeek-R1DeepSeek-R1 $1.18 · GLM-5.1 $2.15 per 1M tokens (3:1 blend)
- Longest contextGLM-5.1GLM-5.1 200,000 · DeepSeek-R1 128,000 tokens
- Widest inputsSame inputsGLM-5.1: Text · DeepSeek-R1: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | GLM-5.1 | DeepSeek-R1 |
|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 78 | 64 |
| Price | 25% | 34 | 47 |
| Inputs & features | 15% | 45 | 35 |
| Context window | 10% | 32 | 24 |
| Overall | 100% | 57/100 | 51/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | GLM-5.1Z.ai (Zhipu) | DeepSeek-R1DeepSeek |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | 149.9 (best) | 139.0 |
| ECI rank | #51 of 148 (best) | #104 of 148 |
| GPQA DiamondGraduate-level science questions | 89.9% (best) | 71.7% |
| FrontierMath Tiers 1–3Research-level mathematics | 36.8% | — |
| OTIS Mock AIME 2024–2025Competition mathematics | 93.3% (best) | 53.3% |
| SWE-bench VerifiedFixing real GitHub issues | 74.2% | — |
| SimpleQA VerifiedShort factual questions | 34.0% | — |
| Price per million tokens | ||
| Input | $1.40 | $0.70 (best) |
| Output | $4.40 | $2.60 (best) |
| Cached input | $0.26 | — |
| Blended (3:1) | $2.15 | $1.18 (best) |
| Long-context rate | Same rate | Same rate |
| Price source | Official Z.AI API | Median of 11 providers |
| Limits | ||
| Context window | 200,000 tokens (best) | 128,000 tokens |
| Max output | 131,072 tokens (best) | 32,768 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | No | No |
| PDFs | No | No |
| Audio | No | No |
| Video | No | No |
| Reasoning | Yes | Yes |
| Tool calling | Yes | Yes |
| Structured output | Yes | No |
| Availability | ||
| Weights | Open | Open |
| API model ID | glm-5.1 | — |
| API providers | 40 (best) | 12 |
| Released | Apr 7, 2026 | Jan 20, 2025 |
| Knowledge cutoff | — | Jul 2024 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- GLM-5.1$22.80
- DeepSeek-R1$12.20
Which should you choose?
Which is better: GLM-5.1 or DeepSeek-R1?
GLM-5.1 is the better all-round choice, scoring 57/100 against DeepSeek-R1 (51). It leads on capability, inputs & features and context window. DeepSeek-R1 wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, GLM-5.1 or DeepSeek-R1?
DeepSeek-R1 is cheaper at $0.70 input / $2.60 output per million tokens (median across 11 API providers). GLM-5.1 costs $1.40 input / $4.40 output per million tokens (official Z.AI API price). At a typical mix of three input tokens to one output token, that is $1.18 per million tokens for DeepSeek-R1 versus $2.15 for GLM-5.1 (1.8× as much).
Which scores higher on benchmarks?
GLM-5.1 scores higher on the Capabilities Index (ECI): GLM-5.1 149.9 (#51 of 148) and DeepSeek-R1 139.0 (#104 of 148). Their confidence ranges do not overlap (148.0–151.6 vs 136.2–140.4), so the gap is a real one. On individual benchmarks: GPQA Diamond — GLM-5.1 89.9%, DeepSeek-R1 71.7%; OTIS Mock AIME 2024–2025 — GLM-5.1 93.3%, DeepSeek-R1 53.3%.
Which is better for coding?
There are no published SWE-bench Verified results for DeepSeek-R1 yet, so there is no like-for-like coding score. On overall capability, GLM-5.1 leads, which tends to carry over to coding, but test on your own codebase. Both support tool calling for agent workflows.
Which has the bigger context window?
GLM-5.1 has the largest context window at 200,000 tokens, against 128,000 for DeepSeek-R1. Maximum output per response: GLM-5.1 up to 131,072, DeepSeek-R1 up to 32,768 tokens.
Which can read images, PDFs, audio or video?
GLM-5.1 accepts text; DeepSeek-R1 accepts text. They handle the same number of input types.
Are any of these open source?
Yes, both publish their weights, so you can self-host them.
Which is newer?
GLM-5.1 is the newest, released Apr 7, 2026. DeepSeek-R1 came out Jan 20, 2025. Knowledge cutoff: DeepSeek-R1 Jul 2024.
How do you decide the winner?
Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Oct 4, 2026.
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