DeepSeek R1 0528 vs GLM-4.7 vs Claude Haiku 4.5
Too close to call on our weighted score (Claude Haiku 4.5 57, GLM-4.7 55, DeepSeek R1 0528 53). The right pick depends on what you value most.
DeepSeek
DeepSeek R1 0528
53/100- ECI141.2
- Price$0.512 / $2.19
- Context164K
Z.ai (Zhipu)
GLM-4.7
55/100- ECI143.7
- Price$0.60 / $2.20
- Context205K
Anthropic
Claude Haiku 4.5
57/100- ECI142.2
- Price$1.00 / $5.00
- Context200K
Too close to call
It is close. Our weighted score puts them within 2 points (Claude Haiku 4.5 57/100, GLM-4.7 55/100, DeepSeek R1 0528 53/100), so choose by what matters most for your work: GLM-4.7 for raw capability and DeepSeek R1 0528 on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityGLM-4.7Capabilities Index (ECI): GLM-4.7 143.7 · Claude Haiku 4.5 142.2 · DeepSeek R1 0528 141.2
- Lowest priceDeepSeek R1 0528DeepSeek R1 0528 $0.932 · GLM-4.7 $1.00 · Claude Haiku 4.5 $2.00 per 1M tokens (3:1 blend)
- Longest contextGLM-4.7GLM-4.7 204,800 · Claude Haiku 4.5 200,000 · DeepSeek R1 0528 163,840 tokens
- Widest inputsClaude Haiku 4.5DeepSeek R1 0528: Text · GLM-4.7: Text · Claude Haiku 4.5: Text, Images, PDFs
- Self-hostingDeepSeek R1 0528 and GLM-4.7Publishes downloadable weights (MIT)
| Measure | Weight | DeepSeek R1 0528 | GLM-4.7 | Claude Haiku 4.5 |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 66 | 69 | 67 |
| Price | 25% | 49 | 48 | 34 |
| Inputs & features | 15% | 35 | 35 | 80 |
| Context window | 10% | 28 | 32 | 32 |
| Overall | 100% | 53/100 | 55/100 | 57/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | |||
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 141.2 | 143.7 (best) | 142.2 |
| ECI rank | #108 of 165 | #94 of 165 (best) | #102 of 165 |
| GPQA DiamondGraduate-level science questions | 76.3% | 83.3% (best) | 71.2% |
| OTIS Mock AIME 2024–2025Competition mathematics | 66.4% | 83.3% (best) | 66.7% |
| SimpleQA VerifiedShort factual questions | — | 32.2% (best) | 13.2% |
| Price per million tokens | |||
| Input | $0.512 (best) | $0.60 | $1.00 |
| Output | $2.19 (best) | $2.20 | $5.00 |
| Cached input | — | $0.11 | $0.10 (best) |
| Blended (3:1) | $0.932 (best) | $1.00 | $2.00 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 16 providers | Official Z.AI API | Official Anthropic API |
| Limits | |||
| Context window | 163,840 tokens | 204,800 tokens (best) | 200,000 tokens |
| Max output | 32,768 tokens | 131,072 tokens (best) | 64,000 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | Yes |
| PDFs | No | No | Yes |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | Yes | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | Yes |
| Availability | |||
| Weights | OpenMIT | Open | Proprietary |
| API model ID | — | glm-4.7 | claude-haiku-4-5 |
| API providers | 16 | 31 | 48 (best) |
| Released | May 28, 2025 | Dec 22, 2025 | Oct 15, 2025 |
| Knowledge cutoff | — | Apr 2025 | Feb 28, 2025 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
DeepSeek R1 0528$9.50
GLM-4.7$10.40
Claude Haiku 4.5$20.00
Which should you choose?
Which is better: DeepSeek R1 0528, GLM-4.7 or Claude Haiku 4.5?
It is close. Our weighted score puts them within 2 points (Claude Haiku 4.5 57/100, GLM-4.7 55/100, DeepSeek R1 0528 53/100), so choose by what matters most for your work: GLM-4.7 for raw capability and DeepSeek R1 0528 on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, DeepSeek R1 0528, GLM-4.7 or Claude Haiku 4.5?
DeepSeek R1 0528 is cheaper at $0.512 input / $2.19 output per million tokens (median across 16 API providers). GLM-4.7 costs $0.60 input / $2.20 output per million tokens (official Z.AI API price); Claude Haiku 4.5 costs $1.00 input / $5.00 output per million tokens (official Anthropic API price). At a typical mix of three input tokens to one output token, that is $0.932 per million tokens for DeepSeek R1 0528 versus $1.00 for GLM-4.7 (1.1× as much) and $2.00 for Claude Haiku 4.5 (2.1× as much).
Which scores higher on benchmarks?
GLM-4.7 scores higher on the Capabilities Index (ECI): GLM-4.7 143.7 (#94 of 165), Claude Haiku 4.5 142.2 (#102 of 165) and DeepSeek R1 0528 141.2 (#108 of 165). The confidence ranges of the top two overlap (141.4–145.8 vs 139.4–143.9), so treat the gap as small. On individual benchmarks: GPQA Diamond — GLM-4.7 83.3%, DeepSeek R1 0528 76.3%, Claude Haiku 4.5 71.2%; OTIS Mock AIME 2024–2025 — GLM-4.7 83.3%, Claude Haiku 4.5 66.7%, DeepSeek R1 0528 66.4%.
Which is better for coding?
There are no published SWE-bench Verified results for DeepSeek R1 0528, GLM-4.7 and Claude Haiku 4.5 yet, so there is no like-for-like coding score. On overall capability, GLM-4.7 leads, which tends to carry over to coding, but test on your own codebase. All three support tool calling for agent workflows.
Which has the bigger context window?
GLM-4.7 has the largest context window at 204,800 tokens, against 200,000 for Claude Haiku 4.5 and 163,840 for DeepSeek R1 0528. Maximum output per response: DeepSeek R1 0528 up to 32,768, GLM-4.7 up to 131,072, Claude Haiku 4.5 up to 64,000 tokens.
Which can read images, PDFs, audio or video?
DeepSeek R1 0528 accepts text; GLM-4.7 accepts text; Claude Haiku 4.5 accepts text, images and PDFs. Claude Haiku 4.5 handles the widest range of inputs.
Are any of these open source?
DeepSeek R1 0528 and GLM-4.7 publishes its weights (MIT) and can be self-hosted; Claude Haiku 4.5 is proprietary.
Which is newer?
GLM-4.7 is the newest, released Dec 22, 2025. Claude Haiku 4.5 came out Oct 15, 2025; DeepSeek R1 0528 came out May 28, 2025. Knowledge cutoff: GLM-4.7 Apr 2025, Claude Haiku 4.5 Feb 28, 2025.
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 Nov 2, 2026.