Claude Haiku 5.5 vs Qwen3.7 Plus
Compare Claude Haiku 5.5 and Qwen3.7 Plus side-by-side.
Compare Claude Haiku 5.5 vs Qwen3.7 Plus live
Run the same image across every model that supports a task and compare their outputs side-by-side.
These models don't share enough common tasks for a side-by-side demo. See the comparison table below for their capabilities.
Models in this comparison
Claude Haiku 5.5 vs Qwen3.7 Plus on Vision Evals
Claude Haiku 5.5 scores higher on 5 of the six Vision Evals tasks.
The widest gap is Reasoning, where Claude Haiku 5.5 leads 68.9% to 39.7%.
Overall, Claude Haiku 5.5 averages 77.2% (#20 of 61) against 67.4% (#37 of 61) for Qwen3.7 Plus.
Claude Haiku 5.5 is cheaper ($0.0005 vs $0.0008 per sample), while Qwen3.7 Plus is faster (7.0s vs 13.2s per sample).
Claude Haiku 5.5 vs Qwen3.7 Plus Comparison Table
Evals updated October 8, 2026Pricing updated October 8, 2026
| Property | Claude Haiku 5.5 | Qwen3.7 Plus |
|---|---|---|
| Organization | Anthropic | Qwen |
| Category | closed | closed |
| Modality | multimodal | — |
| Release Date | Oct 2026 | Jun 2026 |
| Context Window | 1.0M | — |
| Parameters | undisclosed | Unknown |
| License | Proprietary | Unknown |
| Pricing per 1M tokens | ||
| Input $/1M | $0.100 | $0.320 |
| Output $/1M | $0.500 | $1.28 |
| Vision Tasks | ||
| Captioning | Supported | Demo |
| Classification | Supported | Demo |
| Object Detection | Supported | Demo |
| OCR | Supported | Demo |
| Visual Question Answering | Supported | Demo |
| Chart Question Answering | Supported | Not listed |
| Document Question Answering | Supported | Not listed |
| Image Tagging | Supported | Not listed |
| Multi-Label Classification | Supported | Not listed |
| Vision Language | Supported | Not listed |
| Model Features | ||
| Foundation Vision | Supported | Not listed |
| LLMs with Vision Capabilities | Supported | Not listed |
| Multimodal Vision | Supported | Not listed |
Vision Evalsground-truth scores across 6 vision tasks, pooled at low effort | ||
| Overall | 77.2% | 67.4% |
| Avg cost / sample | $0.0005 | $0.0008 |
| Avg speed / sample | 13.23s | 7.01s |
| By task | ||
| Object Detection (low) | 65.8% ±0.6, Mean of 3 runs, range 65.1 to 66.2 | 60.1% |
| Object Detection (high) | 68.2% ±1.0, Mean of 3 runs, range 67.2 to 69.2 | – |
| Counting (low) | 68.9% ±4.7, Mean of 3 runs, range 64.9 to 74.3 | 50.0% |
| Counting (high) | 73.0% ±1.3, Mean of 3 runs, range 71.6 to 74.3 | – |
| Identification (low) | 83.3% ±3.1, Mean of 3 runs, range 81.3 to 87.5 | 84.4% |
| Identification (high) | 86.5% ±1.6, Mean of 3 runs, range 84.4 to 87.5 | – |
| OCR (low) | 90.1% ±1.1, Mean of 3 runs, range 88.8 to 91.0 | 86.5% |
| OCR (high) | 88.0% ±1.3, Mean of 3 runs, range 87.0 to 89.6 | – |
| Data Extraction (low) | 85.9% ±1.5, Mean of 3 runs, range 84.5 to 87.6 | 83.5% |
| Data Extraction (high) | 87.3% ±0.5, Mean of 3 runs, range 86.6 to 87.6 | – |
| Reasoning (low) | 68.9% ±2.0, Mean of 3 runs, range 66.9 to 70.9 | 39.7% |
| Reasoning (high) | 74.8% ±2.6, Mean of 3 runs, range 72.2 to 77.5 | 68.2% |
Claude Haiku 5.5 vs Qwen3.7 Plus: Overview
Claude Haiku 5.5 is a proprietary multimodal language model from Anthropic and the smallest member of the Claude 5.5 family, released on October 7, 2026 after Claude Opus 5.5 and Claude Sonnet 5.5. It accepts text and image input and returns text, with a 1M token context window and up to 128K output tokens per request. It is the first Haiku-class model with an adjustable effort parameter: adaptive thinking is on by default and the model decides how much to reason, steered by effort levels from low to max with medium as the default. Its training data cutoff is June 2026. Pricing starts at $0.10 per million input tokens and $0.50 per million output tokens for prompts up to 100K tokens, which Anthropic reports is about 90% lower than Claude Haiku 4.5 for requests in that range.
Anthropic positions Haiku 5.5 for high-volume, latency-sensitive work such as classification, extraction, routing, summarization, and subagent tasks, and describes it as its fastest model to date at standard speed. On visual and agentic evaluations reported at launch, it scores 46.4% on Chartography, a chart reading benchmark, compared with 6.4% for Haiku 4.5 and 61.6% for Sonnet 5.5, and 72.4% on the offline subset of OSWorld 2.1, a screenshot driven computer use benchmark, compared with 15.7% for Haiku 4.5. It uses the same tokenizer as Claude Opus 4.7 and later models, so the same text counts as roughly 30% more tokens than on Haiku 4.5.
Frequently Asked Questions
On Roboflow's Vision Evals, Claude Haiku 5.5 performed better. It scores higher on 5 of the six vision tasks and averages 77.2% (#20 of 61) against 67.4% (#37 of 61) for Qwen3.7 Plus. These scores measure vision capabilities only; either model may perform differently on work outside this benchmark's tasks.
Yes. On the Vision Evals Reasoning benchmark at low effort, Claude Haiku 5.5 leads with 68.9% against 39.7%. This is the widest gap between the two models across the benchmark's tasks.
Claude Haiku 5.5 is cheaper to run. Across Roboflow's Vision Evals task mix it averaged $0.0005 per sample against $0.0008. Claude Haiku 5.5 is priced at $0.10 per 1M input tokens and $0.50 per 1M output; Qwen3.7 Plus is priced at $0.32 per 1M input tokens and $1.28 per 1M output. Actual costs depend on your image sizes, prompts, and output length.
Qwen3.7 Plus is faster. Across Roboflow's Vision Evals it averaged 7.0s per inference against 13.2s. Latency varies with image size, prompt length, and provider load, so treat these as relative rather than guaranteed figures.