GLM-4.7 vs Claude Haiku 4.5 vs Qwen3.5 Flash
Qwen3.5 Flash comes out ahead, 73 to 57 and 55 on our weighted score, and it is the cheaper option too.
Z.ai (Zhipu)GLM-4.7
55/100- ECI143.7
- Price$0.60 / $2.20
- Context205K
AnthropicClaude Haiku 4.5
57/100- ECI142.2
- Price$1.00 / $5.00
- Context200K
- Our pick
Alibaba (Qwen)Qwen3.5 Flash
73/100- ECI143.6
- Price$0.10 / $0.40
- Context1M
Qwen3.5 Flash is our pick
Qwen3.5 Flash is the better all-round choice, scoring 73/100 against Claude Haiku 4.5 (57) and GLM-4.7 (55). It leads on price and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityGLM-4.7Capabilities Index (ECI): GLM-4.7 143.7 · Qwen3.5 Flash 143.6 · Claude Haiku 4.5 142.2
- Lowest priceQwen3.5 FlashQwen3.5 Flash $0.175 · GLM-4.7 $1.00 · Claude Haiku 4.5 $2.00 per 1M tokens (3:1 blend)
- Longest contextQwen3.5 FlashQwen3.5 Flash 1,000,000 · GLM-4.7 204,800 · Claude Haiku 4.5 200,000 tokens
- Widest inputsClaude Haiku 4.5 and Qwen3.5 FlashGLM-4.7: Text · Claude Haiku 4.5: Text, Images, PDFs · Qwen3.5 Flash: Text, Images, Video
- Self-hostingGLM-4.7Publishes downloadable weights
| Measure | Weight | GLM-4.7 | Claude Haiku 4.5 | Qwen3.5 Flash |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 69 | 67 | 69 |
| Price | 25% | 48 | 34 | 82 |
| Inputs & features | 15% | 35 | 80 | 80 |
| Context window | 10% | 32 | 32 | 60 |
| Overall | 100% | 55/100 | 57/100 | 73/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | GLM-4.7Z.ai (Zhipu) | Claude Haiku 4.5Anthropic | Qwen3.5 FlashAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 143.7 (best) | 142.2 | 143.6 |
| ECI rank | #94 of 165 (best) | #102 of 165 | #95 of 165 |
| GPQA DiamondGraduate-level science questions | 83.3% (best) | 71.2% | 82.3% |
| FrontierMath Tiers 1–3Research-level mathematics | — | — | 18.3% |
| OTIS Mock AIME 2024–2025Competition mathematics | 83.3% | 66.7% | 84.4% (best) |
| SimpleQA VerifiedShort factual questions | 32.2% (best) | 13.2% | 20.3% |
| Price per million tokens | |||
| Input | $0.60 | $1.00 | $0.10 (best) |
| Output | $2.20 | $5.00 | $0.40 (best) |
| Cached input | $0.11 | $0.10 | $0.01 (best) |
| Blended (3:1) | $1.00 | $2.00 | $0.175 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Z.AI API | Official Anthropic API | Official Alibaba API |
| Limits | |||
| Context window | 204,800 tokens | 200,000 tokens | 1,000,000 tokens (best) |
| Max output | 131,072 tokens (best) | 64,000 tokens | 65,536 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | Yes |
| PDFs | No | Yes | No |
| Audio | No | No | No |
| Video | No | No | Yes |
| Reasoning | Yes | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | Yes | Yes |
| Availability | |||
| Weights | Open | Proprietary | Proprietary |
| API model ID | glm-4.7 | claude-haiku-4-5 | qwen3.5-flash |
| API providers | 31 | 48 (best) | 9 |
| Released | Dec 22, 2025 | Oct 15, 2025 | Feb 23, 2026 |
| 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.
- GLM-4.7$10.40
- Claude Haiku 4.5$20.00
- Qwen3.5 Flash$1.80
Which should you choose?
Which is better: GLM-4.7, Claude Haiku 4.5 or Qwen3.5 Flash?
Qwen3.5 Flash is the better all-round choice, scoring 73/100 against Claude Haiku 4.5 (57) and GLM-4.7 (55). It leads on price and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, GLM-4.7, Claude Haiku 4.5 or Qwen3.5 Flash?
Qwen3.5 Flash is cheaper at $0.10 input / $0.40 output per million tokens (official Alibaba API price). 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 $0.175 per million tokens for Qwen3.5 Flash versus $1.00 for GLM-4.7 (5.7× as much) and $2.00 for Claude Haiku 4.5 (11× 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), Qwen3.5 Flash 143.6 (#95 of 165) and Claude Haiku 4.5 142.2 (#102 of 165). The confidence ranges of the top two overlap (141.4–145.8 vs 141.4–145.0), so treat the gap as small. On individual benchmarks: GPQA Diamond — GLM-4.7 83.3%, Qwen3.5 Flash 82.3%, Claude Haiku 4.5 71.2%; OTIS Mock AIME 2024–2025 — Qwen3.5 Flash 84.4%, GLM-4.7 83.3%, Claude Haiku 4.5 66.7%; SimpleQA Verified — GLM-4.7 32.2%, Qwen3.5 Flash 20.3%, Claude Haiku 4.5 13.2%.
Which is better for coding?
There are no published SWE-bench Verified results for GLM-4.7, Claude Haiku 4.5 and Qwen3.5 Flash 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?
Qwen3.5 Flash has the largest context window at 1,000,000 tokens, against 204,800 for GLM-4.7 and 200,000 for Claude Haiku 4.5. Maximum output per response: GLM-4.7 up to 131,072, Claude Haiku 4.5 up to 64,000, Qwen3.5 Flash up to 65,536 tokens.
Which can read images, PDFs, audio or video?
GLM-4.7 accepts text; Claude Haiku 4.5 accepts text, images and PDFs; Qwen3.5 Flash accepts text, images and video. Claude Haiku 4.5 handles the widest range of inputs.
Are any of these open source?
GLM-4.7 publishes its weights and can be self-hosted; Claude Haiku 4.5 and Qwen3.5 Flash is proprietary.
Which is newer?
Qwen3.5 Flash is the newest, released Feb 23, 2026. GLM-4.7 came out Dec 22, 2025; Claude Haiku 4.5 came out Oct 15, 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.
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