GLM-4.7 vs Claude Haiku 4.5 vs Qwen3 Omni 30B A3B Thinking
Qwen3 Omni 30B A3B Thinking comes out ahead, 59 to 47 and 41 on our weighted score, and it is the cheaper option too.
Z.ai (Zhipu)GLM-4.7
41/100- ECI143.7
- Price$0.60 / $2.20
- Context205K
AnthropicClaude Haiku 4.5
47/100- ECI142.2
- Price$1.00 / $5.00
- Context200K
- Our pick
Alibaba (Qwen)Qwen3 Omni 30B A3B Thinking
59/100- ECI—
- Price$0.25 / $0.97
- Context66K
Qwen3 Omni 30B A3B Thinking is our pick
Qwen3 Omni 30B A3B Thinking is the better all-round choice, scoring 59/100 against Claude Haiku 4.5 (47) and GLM-4.7 (41). It leads on price. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
- CapabilityNot enough dataNo independent benchmark covers every model here yet
- Lowest priceQwen3 Omni 30B A3B ThinkingQwen3 Omni 30B A3B Thinking $0.43 · 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 · Qwen3 Omni 30B A3B Thinking 65,536 tokens
- Widest inputsQwen3 Omni 30B A3B ThinkingGLM-4.7: Text · Claude Haiku 4.5: Text, Images, PDFs · Qwen3 Omni 30B A3B Thinking: Text, Images, Audio, Video
- Self-hostingGLM-4.7 and Qwen3 Omni 30B A3B ThinkingPublishes downloadable weights (Apache-2.0)
| Measure | Weight | GLM-4.7 | Claude Haiku 4.5 | Qwen3 Omni 30B A3B Thinking |
|---|---|---|---|---|
| Price | 50% | 48 | 34 | 64 |
| Inputs & features | 30% | 35 | 80 | 80 |
| Context window | 20% | 32 | 32 | 12 |
| Overall | 100% | 41/100 | 47/100 | 59/100 |
Left out because at least one model lacks the data: capability. The remaining weights were rescaled.
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 Omni 30B A3B ThinkingAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 143.7 (best) | 142.2 | — |
| ECI rank | #94 of 165 (best) | #102 of 165 | — |
| GPQA DiamondGraduate-level science questions | 83.3% (best) | 71.2% | — |
| OTIS Mock AIME 2024–2025Competition mathematics | 83.3% (best) | 66.7% | — |
| SimpleQA VerifiedShort factual questions | 32.2% (best) | 13.2% | — |
| Price per million tokens | |||
| Input | $0.60 | $1.00 | $0.25 (best) |
| Output | $2.20 | $5.00 | $0.97 (best) |
| Cached input | $0.11 | $0.10 (best) | — |
| Blended (3:1) | $1.00 | $2.00 | $0.43 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Z.AI API | Official Anthropic API | Median of 1 providers |
| Limits | |||
| Context window | 204,800 tokens (best) | 200,000 tokens | 65,536 tokens |
| Max output | 131,072 tokens (best) | 64,000 tokens | 16,384 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | Yes |
| PDFs | No | Yes | No |
| Audio | No | No | Yes |
| Video | No | No | Yes |
| Reasoning | Yes | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | Yes | No |
| Availability | |||
| Weights | Open | Proprietary | OpenApache-2.0 |
| API model ID | glm-4.7 | claude-haiku-4-5 | — |
| API providers | 31 | 48 (best) | 1 |
| Released | Dec 22, 2025 | Oct 15, 2025 | Sep 22, 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.
- GLM-4.7$10.40
- Claude Haiku 4.5$20.00
- Qwen3 Omni 30B A3B Thinking$4.44
Which should you choose?
Which is better: GLM-4.7, Claude Haiku 4.5 or Qwen3 Omni 30B A3B Thinking?
Qwen3 Omni 30B A3B Thinking is the better all-round choice, scoring 59/100 against Claude Haiku 4.5 (47) and GLM-4.7 (41). It leads on price. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, GLM-4.7, Claude Haiku 4.5 or Qwen3 Omni 30B A3B Thinking?
Qwen3 Omni 30B A3B Thinking is cheaper at $0.25 input / $0.97 output per million tokens (median across 1 API provider). 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 $0.43 per million tokens for Qwen3 Omni 30B A3B Thinking versus $1.00 for GLM-4.7 (2.3× as much) and $2.00 for Claude Haiku 4.5 (4.7× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. GLM-4.7 has an ECI of 143.7, Claude Haiku 4.5 has an ECI of 142.2 and Qwen3 Omni 30B A3B Thinking has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for GLM-4.7, Claude Haiku 4.5 and Qwen3 Omni 30B A3B Thinking yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. 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 65,536 for Qwen3 Omni 30B A3B Thinking. Maximum output per response: GLM-4.7 up to 131,072, Claude Haiku 4.5 up to 64,000, Qwen3 Omni 30B A3B Thinking up to 16,384 tokens.
Which can read images, PDFs, audio or video?
GLM-4.7 accepts text; Claude Haiku 4.5 accepts text, images and PDFs; Qwen3 Omni 30B A3B Thinking accepts text, images, audio and video. Qwen3 Omni 30B A3B Thinking handles the widest range of inputs.
Are any of these open source?
GLM-4.7 and Qwen3 Omni 30B A3B Thinking publishes its weights (Apache-2.0) 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; Qwen3 Omni 30B A3B Thinking came out Sep 22, 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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