Claude Haiku 4.5 vs Grok 4.1 Fast vs GLM-4.7
Grok 4.1 Fast comes out ahead, 66 to 47 and 41 on our weighted score, and it is the cheaper option too.
AnthropicClaude Haiku 4.5
47/100- ECI142.2
- Price$1.00 / $5.00
- Context200K
- Our pick
xAIGrok 4.1 Fast
66/100- ECI—
- Price$0.20 / $0.50
- Context2M
Z.ai (Zhipu)GLM-4.7
41/100- ECI143.7
- Price$0.60 / $2.20
- Context205K
Grok 4.1 Fast is our pick
Grok 4.1 Fast is the better all-round choice, scoring 66/100 against Claude Haiku 4.5 (47) and GLM-4.7 (41). It leads on price and context window. Claude Haiku 4.5 wins on inputs & features. 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 priceGrok 4.1 FastGrok 4.1 Fast $0.275 · GLM-4.7 $1.00 · Claude Haiku 4.5 $2.00 per 1M tokens (3:1 blend)
- Longest contextGrok 4.1 FastGrok 4.1 Fast 2,000,000 · GLM-4.7 204,800 · Claude Haiku 4.5 200,000 tokens
- Widest inputsClaude Haiku 4.5Claude Haiku 4.5: Text, Images, PDFs · Grok 4.1 Fast: Text, Images · GLM-4.7: Text
- Self-hostingGLM-4.7Publishes downloadable weights
| Measure | Weight | Claude Haiku 4.5 | Grok 4.1 Fast | GLM-4.7 |
|---|---|---|---|---|
| Price | 50% | 34 | 73 | 48 |
| Inputs & features | 30% | 80 | 50 | 35 |
| Context window | 20% | 32 | 72 | 32 |
| Overall | 100% | 47/100 | 66/100 | 41/100 |
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 | Claude Haiku 4.5Anthropic | Grok 4.1 FastxAI | GLM-4.7Z.ai (Zhipu) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 142.2 | — | 143.7 (best) |
| ECI rank | #102 of 165 | — | #94 of 165 (best) |
| GPQA DiamondGraduate-level science questions | 71.2% | — | 83.3% (best) |
| OTIS Mock AIME 2024–2025Competition mathematics | 66.7% | — | 83.3% (best) |
| SimpleQA VerifiedShort factual questions | 13.2% | — | 32.2% (best) |
| Price per million tokens | |||
| Input | $1.00 | $0.20 (best) | $0.60 |
| Output | $5.00 | $0.50 (best) | $2.20 |
| Cached input | $0.10 (best) | — | $0.11 |
| Blended (3:1) | $2.00 | $0.275 (best) | $1.00 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Anthropic API | Median of 6 providers | Official Z.AI API |
| Limits | |||
| Context window | 200,000 tokens | 2,000,000 tokens (best) | 204,800 tokens |
| Max output | 64,000 tokens | 30,000 tokens | 131,072 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | No |
| PDFs | Yes | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | Yes | No | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | No | No |
| Availability | |||
| Weights | Proprietary | Proprietary | Open |
| API model ID | claude-haiku-4-5 | — | glm-4.7 |
| API providers | 48 (best) | 8 | 31 |
| Released | Oct 15, 2025 | Nov 19, 2025 | Dec 22, 2025 |
| Knowledge cutoff | Feb 28, 2025 | — | Apr 2025 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Claude Haiku 4.5$20.00
- Grok 4.1 Fast$3.00
- GLM-4.7$10.40
Which should you choose?
Which is better: Claude Haiku 4.5, Grok 4.1 Fast or GLM-4.7?
Grok 4.1 Fast is the better all-round choice, scoring 66/100 against Claude Haiku 4.5 (47) and GLM-4.7 (41). It leads on price and context window. Claude Haiku 4.5 wins on inputs & features. 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, Claude Haiku 4.5, Grok 4.1 Fast or GLM-4.7?
Grok 4.1 Fast is cheaper at $0.20 input / $0.50 output per million tokens (median across 6 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 $0.275 per million tokens for Grok 4.1 Fast versus $1.00 for GLM-4.7 (3.6× as much) and $2.00 for Claude Haiku 4.5 (7.3× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Claude Haiku 4.5 has an ECI of 142.2, Grok 4.1 Fast has not been scored yet and GLM-4.7 has an ECI of 143.7.
Which is better for coding?
There are no published SWE-bench Verified results for Claude Haiku 4.5, Grok 4.1 Fast and GLM-4.7 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?
Grok 4.1 Fast has the largest context window at 2,000,000 tokens, against 204,800 for GLM-4.7 and 200,000 for Claude Haiku 4.5. Maximum output per response: Claude Haiku 4.5 up to 64,000, Grok 4.1 Fast up to 30,000, GLM-4.7 up to 131,072 tokens.
Which can read images, PDFs, audio or video?
Claude Haiku 4.5 accepts text, images and PDFs; Grok 4.1 Fast accepts text and images; GLM-4.7 accepts text. 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 Grok 4.1 Fast is proprietary.
Which is newer?
GLM-4.7 is the newest, released Dec 22, 2025. Grok 4.1 Fast came out Nov 19, 2025; Claude Haiku 4.5 came out Oct 15, 2025. Knowledge cutoff: Claude Haiku 4.5 Feb 28, 2025, GLM-4.7 Apr 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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