# LBS-27B vs WeVisOne-VL-4B

> WeVisOne-VL-4B scores 61 (C) to LBS-27B's 55.8 (C) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/lbs-27b-vs-wevisone-vl-4b
- Markdown: https://www.anchorterminal.com/compare/lbs-27b-vs-wevisone-vl-4b.md (~8,850 tokens)
- Site index for agents: https://www.anchorterminal.com/llms.txt (the key docs and every listing in one file, at most 16 MB, about 4 million tokens: https://www.anchorterminal.com/llms-full.txt)
- API: https://www.anchorterminal.com/api/v1/index.json
- MCP: https://www.anchorterminal.com/mcp (the whole catalogue as tools, no key)
- DNS: dig +short TXT <slug>.grade.anchorterminal.com (the grade as a DNS TXT record, for a sandbox with no HTTP where names still resolve; also top., best.<category>. and <a>.vs.<b>. under the zone, and the same under grade.letme.dev)
- Licence: CC BY 4.0, credit Anchor Terminal and link this page (https://www.anchorterminal.com/terms/#data)
- Updated: 2026-11-10

WeVisOne-VL-4B scores 61 (C) on agent readiness against LBS-27B's 55.8 (C), and leads in 3 of 4 scored categories. Both do open-weight models you run yourself.

- LBS-27B: grade C, 55.8/100, rank #118 of 160 open-weight models. Markdown https://www.anchorterminal.com/tools/lbs-27b.md · JSON https://www.anchorterminal.com/api/v1/tools/lbs-27b.json
- WeVisOne-VL-4B: grade C, 61/100, rank #84 of 160 open-weight models. Markdown https://www.anchorterminal.com/tools/wevisone-vl-4b.md · JSON https://www.anchorterminal.com/api/v1/tools/wevisone-vl-4b.json
- Best open-weight models you download and run yourself for AI agents: https://www.anchorterminal.com/best/open-weights/index.md
- All 6359 open weights comparisons: https://www.anchorterminal.com/compare/open-weights/index.md

## Which one, for what

### LBS-27B (C)

Good for: Agents with about 96 GB of GPU memory that need to find click targets on dense professional screenshots, or read fine detail in large images, and can run a small crop loop and wait for independent results.

Watch for: No independent benchmark result yet; ScreenSpot-Pro, OS-World-G, PerceptionBench and HR-Bench numbers are inclusionAI's own runs

### WeVisOne-VL-4B (C)

Good for: Agents that need to locate, count or cut out objects in images on a small GPU, under a permissive licence

Ahead on:
- Reach, 70 against 60
- Risk, 55 against 50
- Documentation and upkeep, 48 against 43

Watch for: The pixel decoder ships as a pickle file


## Why the edge

### Reach: WeVisOne-VL-4B +10

- LBS-27B (60): Memory earns 10, since the only build is 54.73 GB of BF16, about 66 GB with a fifth added, which fits the reference machine but not 64 GB. Runtimes earn 25 from released vLLM, SGLang, Transformers and llama.cpp, which all carry Qwen3.8-27B's architecture, and Ollama through the llama.cpp release it pins, so 25. Builds earn 0, as inclusionAI publishes no quantised build and the GGUF copies are bartowski's and mradermacher's. Terms earn 15 for Apache 2.0 with nothing added, on the weights and on the base. Download earns 10, with no gate. Hosted earns 0, as no provider or inclusionAI API serves it.
- WeVisOne-VL-4B (70): Memory 30, the only build from Tencent is the BF16 safetensors file with its decoder, 9.7 GB, and 9.7 GB × 1.2 = 11.6 GB, within 16 GB. No runtime library has a build. Runtimes 15, the architecture is Qwen3VLForConditionalGeneration, which vLLM 0.33.0, SGLang 0.5.23 and Transformers 5.22.2 run from the safetensors file, three at 5 each. Builds 0, Tencent publishes the BF16 weights only. Terms 15, Apache 2.0 in the card's metadata with the LICENSE file in the repository, and nothing added. Download 10, the Hub API reports gated false on 10 November 2026, so the files download with no account and nothing to accept. Hosted 0, Hugging Face maps no inference provider to it. 30 + 15 + 0 + 15 + 10 + 0 = 70.

### Risk: WeVisOne-VL-4B +5

- LBS-27B (50): File safety earns 15, safetensors only but with the documented route running the publisher's scripts to serve it and to write its system prompt. Provenance earns 15, inclusionAI's own organisation with a hash for every file. Safety evaluation and agent guidance earn 0, as nothing is published on either, prompt injection through screenshots included. Licence risk keeps all 15 under Apache 2.0. The security programme earns 5 for Ant Group's AntSRC, which isn't linked to the model.
- WeVisOne-VL-4B (55): File safety 15, the backbone is safetensors, but mask_decoder.pt, a PyTorch pickle the card calls a required component, sits beside it. Provenance 15, the files sit in the tencent organisation, which Tencent's GitHub repository for the model links to (10), and the Hub gives a SHA-256 for the large files (5). Safety evaluation 0, no safety results on the card or in the README. Agent guidance 5, General cautions: the card says the release is for research, isn't for autonomous high-impact decisions or identifying individuals, and lists where masks go wrong. Licence risk 15, Apache 2.0 with no use policy, no threshold and no right to change the terms. Security programme 5, Tencent's Security Response Center takes vulnerability reports company-wide, as the Hy3 listing records (5). 15 + 15 + 0 + 5 + 15 + 5 = 55.

### Documentation and upkeep: WeVisOne-VL-4B +5

- LBS-27B (43): The model card earns 8, with intended use, one limitation and parameters, and no architecture, context, languages or cut-off. Training data earns 5 for a general description of synthetic GUI data with no cut-off. Last change earns 20 for 26 October 2026. Responsiveness earns 0, the one discussion unanswered. Version policy earns 5 for a first release. File health earns 5, as the config still sets an MTP layer the weights lack and the card names a reasoning setting the template refuses.
- WeVisOne-VL-4B (48): Model card 8, Intended use, limitations and the architecture are on the card. Training data 5, A general description in the README of a data engine and over 100 million annotated images, with no sources named and no cut-off. Last change 20, the last commit, on 27 October 2026, added links to the paper and project page, 14 days before this check. Responsiveness 0, Neither of the 2 discussions that aren't pull requests (23 and 26 October 2026) has a reply from a tencent member, counted on 10 November by author flags and dates with a script, text not read. Version policy 5, A first release, 14 days old. File health 10, Config, template and card agree on the Qwen3-VL classes, and the card names mask_decoder.pt as required and it's there. 8 + 5 + 20 + 0 + 5 + 10 = 48.

## Score by category

| Category | Weight | LBS-27B | WeVisOne-VL-4B | Edge |
| --- | --- | --- | --- | --- |
| Capability | 35%, pending | pending | pending | not scored in this run |
| Reach | 25% (25 this run) | 60 | 70 | WeVisOne-VL-4B +10 |
| Risk | 20% (20 this run) | 50 | 55 | WeVisOne-VL-4B +5 |
| Agent interface | 10% (10 this run) | 70 | 70 | even |
| Documentation and upkeep | 10% (10 this run) | 43 | 48 | WeVisOne-VL-4B +5 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **55.8 · C** | **61 · C** | |

## Facts side by side

| Fact | LBS-27B | WeVisOne-VL-4B |
| --- | --- | --- |
| Kind | Open-weight model | Open-weight model |
| Vendor | inclusionAI (Ant Group) | Tencent (WeChat Vision) |
| Hosted endpoint | no (local only) | no (local only) |
| Transports |  |  |
| Auth | None | None |
| Pricing | Free | Free |
| x402 | no | no |
| Licence | Apache-2.0 (the card's metadata and licence section; the LICENSE file sits in the GitHub repository inclusionAI/UI-Venus on its LBS branch, not in the Hugging Face repository) | Apache-2.0 |
| Read-only variant documented | no | no |
| llms.txt | no | no |
| Last release | 2026-10-26 | 2026-10-27 |
| Terms last updated | no document linked | not read yet |
| Privacy policy last updated | no document linked | no document linked |

## How the scores have moved

### LBS-27B

- +1.9 on 4 November 2026 (D to C): correction

### WeVisOne-VL-4B

No score change since it was listed.

## Verdicts

**LBS-27B.** A 27B Qwen3.8 fine-tune for GUI grounding that zooms into screenshots over a few turns before naming a point, and inclusionAI says it also helps with fine detail in large images. It needs about 96 GB at BF16 and a client that runs its crop actions. Every result so far is inclusionAI's own, with no safety results or injection guidance.

**WeVisOne-VL-4B.** A small Apache 2.0 perception model that finds, counts, reads and cuts out what you name in an image, and says None when it isn't there. Boxes and points run in vLLM, SGLang or Transformers. Masks and mattes need Tencent's package and a pickle file. Two weeks old, with no questions answered yet and no safety results.

## Before you call either

### LBS-27B

1. Serve with `vllm serve inclusionAI/LBS-27B --tensor-parallel-size 4 --max-model-len 65536`, which is what the card's wrapper script runs; keep the context at 32,768 or more for multi-turn images
2. Build the system prompt with `build_system_prompt` from the LBS branch's `zoomin_grounding_protocol.py`, send the screenshot after `image_path: <name>`, and don't pass `tools`; the model answers in plain text
3. Parse `<action>crop_image(image_path=..., x1=..., y1=..., x2=..., y2=...)</action>`, cut the crop yourself and return it with its mapping to the original image; allow at most two crops per turn and three per episode
4. Read the final answer as `[x.xx,y.yy]` on a 0 to 1000 scale of the original image, and use your own executor to click
5. Pass `reasoning_effort` as `xhigh`, `medium` or `low` only, since the template raises an error for `high`, and don't count on `thinking_budget`, which the template ignores
6. Don't turn on MTP speculative decoding; the MTP weights aren't in the repository though config.json names one MTP layer

### WeVisOne-VL-4B

1. Use Tencent's package: `WeVisOneVL("tencent/WeVisOne-VL-4B", backend="vllm")` then `model.predict(image, task=..., query=...)`
2. Tasks are detection, referring, point, count_box, count_point, ocr, ocr_grounding, segmentation and matting
3. A None answer means the target isn't in the image. Treat it as a result, not an error
4. mask_decoder.pt is a pickle. Load it only from the tencent repository, and check its SHA-256 against the Hub's
5. Send one image a turn. Video grids are rejected by the decoder
6. The card says it isn't for identifying individuals or for high-impact decisions on its own

## Questions

### Which is better for AI agents, LBS-27B or WeVisOne-VL-4B?

WeVisOne-VL-4B scores 61 (C) on agent readiness against LBS-27B's 55.8 (C), and leads in 3 of 4 scored categories.


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/lbs-27b-vs-wevisone-vl-4b.json, and with the fewest tokens: https://www.anchorterminal.com/compare/lbs-27b-vs-wevisone-vl-4b.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "lbs-27b", "b": "wevisone-vl-4b"}`. From a terminal: `anchor compare lbs-27b wevisone-vl-4b`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/lbs-27b.json and https://www.anchorterminal.com/api/v1/tools/wevisone-vl-4b.json

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- [LBS-27B vs MiniCPM-V 4.7 1B](https://www.anchorterminal.com/compare/lbs-27b-vs-minicpm-v-4-7-1b.md)
- [LBS-27B vs MiniCPM-V 4.7 35B-A3B](https://www.anchorterminal.com/compare/lbs-27b-vs-minicpm-v-4-7-35b-a3b.md)
- [LBS-27B vs MiniCPM5-2B](https://www.anchorterminal.com/compare/lbs-27b-vs-minicpm5-2b.md)
- [LBS-27B vs MiniMax-M2.5](https://www.anchorterminal.com/compare/lbs-27b-vs-minimax-m2-5.md)
- [LBS-27B vs MiniMax-M2.7](https://www.anchorterminal.com/compare/lbs-27b-vs-minimax-m2-7.md)
- [LBS-27B vs MiniMax-M3.1-Flash](https://www.anchorterminal.com/compare/lbs-27b-vs-minimax-m3-1-flash.md)
- [LBS-27B vs Mistral Large 4](https://www.anchorterminal.com/compare/lbs-27b-vs-mistral-large-4.md)
- [LBS-27B vs Muse Glimmer 30B](https://www.anchorterminal.com/compare/lbs-27b-vs-muse-glimmer-30b.md)
- [LBS-27B vs Nanbeige4.2-3B](https://www.anchorterminal.com/compare/lbs-27b-vs-nanbeige-4-2-3b.md)
- [LBS-27B vs Nanbeige4.3-33B](https://www.anchorterminal.com/compare/lbs-27b-vs-nanbeige-4-3-33b.md)
- [LBS-27B vs NVIDIA Nemotron 3.5 Bolt E4B 4GB](https://www.anchorterminal.com/compare/lbs-27b-vs-nemotron-3-5-bolt-e4b-4gb.md)
- [LBS-27B vs Nemotron 3.5 Lightning 30B A3B](https://www.anchorterminal.com/compare/lbs-27b-vs-nemotron-3-5-lightning-30b-a3b.md)
- [LBS-27B vs Nemotron 3 Nano 30B A3B](https://www.anchorterminal.com/compare/lbs-27b-vs-nemotron-3-nano-30b-a3b.md)
- [LBS-27B vs Nemotron 3 Nano 4B](https://www.anchorterminal.com/compare/lbs-27b-vs-nemotron-3-nano-4b.md)
- [LBS-27B vs Nemotron 3 Nano Omni 30B A3B Reasoning](https://www.anchorterminal.com/compare/lbs-27b-vs-nemotron-3-nano-omni-30b-a3b-reasoning.md)
- [LBS-27B vs Nemotron 3 Super 120B A12B](https://www.anchorterminal.com/compare/lbs-27b-vs-nemotron-3-super-120b-a12b.md)
- [LBS-27B vs Nemotron 3 Ultra 550B A55B](https://www.anchorterminal.com/compare/lbs-27b-vs-nemotron-3-ultra-550b-a55b.md)
- [LBS-27B vs North Mini Code 1.0](https://www.anchorterminal.com/compare/lbs-27b-vs-north-mini-code-1-0.md)
- [LBS-27B vs occamy-1.0](https://www.anchorterminal.com/compare/lbs-27b-vs-occamy-1-0.md)
- [LBS-27B vs Olmo 3 7B Think](https://www.anchorterminal.com/compare/lbs-27b-vs-olmo-3-7b-think.md)
- [LBS-27B vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/lbs-27b-vs-ornith-1-5-122b.md)
- [LBS-27B vs Ornith-1.5-35B-A3B](https://www.anchorterminal.com/compare/lbs-27b-vs-ornith-1-5-35b-a3b.md)
- [LBS-27B vs Ornith-1.5-397B](https://www.anchorterminal.com/compare/lbs-27b-vs-ornith-1-5-397b.md)
- [LBS-27B vs Ornith-1.5-9B](https://www.anchorterminal.com/compare/lbs-27b-vs-ornith-1-5-9b.md)
- [LBS-27B vs OTel-2.0-LLM-31B-IT](https://www.anchorterminal.com/compare/lbs-27b-vs-otel-2-0-llm-31b-it.md)
- [LBS-27B vs Qwen-AgentWorld-35B-A3B](https://www.anchorterminal.com/compare/lbs-27b-vs-qwen-agentworld-35b-a3b.md)
- [LBS-27B vs Qwen3-30B-A3B-Instruct-2507](https://www.anchorterminal.com/compare/lbs-27b-vs-qwen3-30b-a3b-instruct-2507.md)
- [LBS-27B vs Qwen3-4B-Instruct-2507](https://www.anchorterminal.com/compare/lbs-27b-vs-qwen3-4b-instruct-2507.md)
- [LBS-27B vs Qwen3.5-0.8B](https://www.anchorterminal.com/compare/lbs-27b-vs-qwen3-5-0-8b.md)
- [LBS-27B vs Qwen3.5-122B-A10B](https://www.anchorterminal.com/compare/lbs-27b-vs-qwen3-5-122b-a10b.md)
- [LBS-27B vs Qwen3.5-2B](https://www.anchorterminal.com/compare/lbs-27b-vs-qwen3-5-2b.md)
- [LBS-27B vs Qwen3.5-397B-A17B](https://www.anchorterminal.com/compare/lbs-27b-vs-qwen3-5-397b-a17b.md)
- [LBS-27B vs Qwen3.5-4B](https://www.anchorterminal.com/compare/lbs-27b-vs-qwen3-5-4b.md)
- [LBS-27B vs Qwen3.5-9B](https://www.anchorterminal.com/compare/lbs-27b-vs-qwen3-5-9b.md)
- [LBS-27B vs Qwen3.6-27B](https://www.anchorterminal.com/compare/lbs-27b-vs-qwen3-6-27b.md)
- [LBS-27B vs Qwen3.6-35B-A3B](https://www.anchorterminal.com/compare/lbs-27b-vs-qwen3-6-35b-a3b.md)
- [LBS-27B vs Qwen3.8-27B](https://www.anchorterminal.com/compare/lbs-27b-vs-qwen3-8-27b.md)
- [LBS-27B vs Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/lbs-27b-vs-qwen3-8-flash-next.md)
- [LBS-27B vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/lbs-27b-vs-qwen3-coder-30b-a3b-instruct.md)
- [LBS-27B vs Qwen3-Coder-Next](https://www.anchorterminal.com/compare/lbs-27b-vs-qwen3-coder-next.md)
- [LBS-27B vs Qwen3-Omni-30B-A3B-Instruct](https://www.anchorterminal.com/compare/lbs-27b-vs-qwen3-omni-30b-a3b-instruct.md)
- [LBS-27B vs Qwen3-VL-2B-Instruct](https://www.anchorterminal.com/compare/lbs-27b-vs-qwen3-vl-2b-instruct.md)
- [LBS-27B vs Qwen3-VL-30B-A3B-Instruct](https://www.anchorterminal.com/compare/lbs-27b-vs-qwen3-vl-30b-a3b-instruct.md)
- [LBS-27B vs Qwen3-VL-32B-Instruct](https://www.anchorterminal.com/compare/lbs-27b-vs-qwen3-vl-32b-instruct.md)
- [LBS-27B vs Qwen3-VL-4B-Instruct](https://www.anchorterminal.com/compare/lbs-27b-vs-qwen3-vl-4b-instruct.md)
- [LBS-27B vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/lbs-27b-vs-qwen3-vl-8b-instruct.md)
- [LBS-27B vs Qwopus3.8-27B-Flash-V2](https://www.anchorterminal.com/compare/lbs-27b-vs-qwopus3-8-27b-flash-v2.md)
- [LBS-27B vs Recursive Flint](https://www.anchorterminal.com/compare/lbs-27b-vs-recursive-flint.md)
- [LBS-27B vs Ripple-65B Preview](https://www.anchorterminal.com/compare/lbs-27b-vs-ripple-65b-preview.md)
- [LBS-27B vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/lbs-27b-vs-sensenova-loop-9b-preview.md)
- [LBS-27B vs SmolLM3-3B](https://www.anchorterminal.com/compare/lbs-27b-vs-smollm3-3b.md)
- [LBS-27B vs Spark-X2.6-4B](https://www.anchorterminal.com/compare/lbs-27b-vs-spark-x2-6-4b.md)
- [LBS-27B vs Step 3.7 Flash](https://www.anchorterminal.com/compare/lbs-27b-vs-step-3-7-flash.md)
- [LBS-27B vs Swift 1.5 Qwen3.8-27B](https://www.anchorterminal.com/compare/lbs-27b-vs-swift-1-5-qwen3-8-27b.md)
- [LBS-27B vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/lbs-27b-vs-swift-1-5-qwen3-8-flash-next.md)
- [LBS-27B vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/lbs-27b-vs-thinkingcap-qwen3-8-27b.md)
- [LBS-27B vs Baidu Unlimited-OCR-2](https://www.anchorterminal.com/compare/lbs-27b-vs-unlimited-ocr-2.md)
- [LBS-27B vs WeVisOne-VL-2B](https://www.anchorterminal.com/compare/lbs-27b-vs-wevisone-vl-2b.md)
- [LBS-27B vs ZAYA1-8B](https://www.anchorterminal.com/compare/lbs-27b-vs-zaya1-8b.md)
- [LFM2.5-2.6B vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/lfm2-5-2-6b-vs-wevisone-vl-4b.md)
- [LFM3-1.7B vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/lfm3-1-7b-vs-wevisone-vl-4b.md)
- [LFM3-Audio-2B vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-wevisone-vl-4b.md)
- [LFM3-Omni-2B vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/lfm3-omni-2b-vs-wevisone-vl-4b.md)
- [LFM3-VL-2B vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/lfm3-vl-2b-vs-wevisone-vl-4b.md)
- [Ling-3.0-tiny vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-wevisone-vl-4b.md)
- [Ling-3.1-flash-1019 vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-wevisone-vl-4b.md)
- [LongCat-2.5 vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/longcat-2-5-vs-wevisone-vl-4b.md)
- [MiMo-V2.6 Distill Qwen 9B vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-wevisone-vl-4b.md)
- [MiMo-V2.6-Flash-RL vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-wevisone-vl-4b.md)
- [MiniCPM-o 4.5 vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-wevisone-vl-4b.md)
- [MiniCPM-V 4.7 1B vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/minicpm-v-4-7-1b-vs-wevisone-vl-4b.md)
- [MiniCPM-V 4.7 35B-A3B vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/minicpm-v-4-7-35b-a3b-vs-wevisone-vl-4b.md)
- [MiniCPM5-2B vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/minicpm5-2b-vs-wevisone-vl-4b.md)
- [MiniMax-M2.5 vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/minimax-m2-5-vs-wevisone-vl-4b.md)
- [MiniMax-M2.7 vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/minimax-m2-7-vs-wevisone-vl-4b.md)
- [MiniMax-M3.1-Flash vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-wevisone-vl-4b.md)
- [Mistral Large 4 vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/mistral-large-4-vs-wevisone-vl-4b.md)
- [Muse Glimmer 30B vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/muse-glimmer-30b-vs-wevisone-vl-4b.md)
- [Nanbeige4.2-3B vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/nanbeige-4-2-3b-vs-wevisone-vl-4b.md)
- [Nanbeige4.3-33B vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/nanbeige-4-3-33b-vs-wevisone-vl-4b.md)
- [NVIDIA Nemotron 3.5 Bolt E4B 4GB vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/nemotron-3-5-bolt-e4b-4gb-vs-wevisone-vl-4b.md)
- [Nemotron 3.5 Lightning 30B A3B vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/nemotron-3-5-lightning-30b-a3b-vs-wevisone-vl-4b.md)
- [Nemotron 3 Nano 30B A3B vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-wevisone-vl-4b.md)
- [Nemotron 3 Nano 4B vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/nemotron-3-nano-4b-vs-wevisone-vl-4b.md)
- [Nemotron 3 Nano Omni 30B A3B Reasoning vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-wevisone-vl-4b.md)
- [Nemotron 3 Super 120B A12B vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-wevisone-vl-4b.md)
- [Nemotron 3 Ultra 550B A55B vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-wevisone-vl-4b.md)
- [North Mini Code 1.0 vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/north-mini-code-1-0-vs-wevisone-vl-4b.md)
- [occamy-1.0 vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/occamy-1-0-vs-wevisone-vl-4b.md)
- [Olmo 3 7B Think vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-wevisone-vl-4b.md)
- [Ornith-1.5-122B vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-wevisone-vl-4b.md)
- [Ornith-1.5-35B-A3B vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/ornith-1-5-35b-a3b-vs-wevisone-vl-4b.md)
- [Ornith-1.5-397B vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/ornith-1-5-397b-vs-wevisone-vl-4b.md)
- [Ornith-1.5-9B vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/ornith-1-5-9b-vs-wevisone-vl-4b.md)
- [OTel-2.0-LLM-31B-IT vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/otel-2-0-llm-31b-it-vs-wevisone-vl-4b.md)
- [Qwen-AgentWorld-35B-A3B vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/qwen-agentworld-35b-a3b-vs-wevisone-vl-4b.md)
- [Qwen3-30B-A3B-Instruct-2507 vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/qwen3-30b-a3b-instruct-2507-vs-wevisone-vl-4b.md)
- [Qwen3-4B-Instruct-2507 vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-wevisone-vl-4b.md)
- [Qwen3.5-0.8B vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/qwen3-5-0-8b-vs-wevisone-vl-4b.md)
- [Qwen3.5-122B-A10B vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/qwen3-5-122b-a10b-vs-wevisone-vl-4b.md)
- [Qwen3.5-2B vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/qwen3-5-2b-vs-wevisone-vl-4b.md)
- [Qwen3.5-397B-A17B vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/qwen3-5-397b-a17b-vs-wevisone-vl-4b.md)
- [Qwen3.5-4B vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/qwen3-5-4b-vs-wevisone-vl-4b.md)
- [Qwen3.5-9B vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/qwen3-5-9b-vs-wevisone-vl-4b.md)
- [Qwen3.6-27B vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/qwen3-6-27b-vs-wevisone-vl-4b.md)
- [Qwen3.6-35B-A3B vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/qwen3-6-35b-a3b-vs-wevisone-vl-4b.md)
- [Qwen3.8-27B vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/qwen3-8-27b-vs-wevisone-vl-4b.md)
- [Qwen3.8-Flash-Next vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/qwen3-8-flash-next-vs-wevisone-vl-4b.md)
- [Qwen3-Coder-30B-A3B-Instruct vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/qwen3-coder-30b-a3b-instruct-vs-wevisone-vl-4b.md)
- [Qwen3-Coder-Next vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/qwen3-coder-next-vs-wevisone-vl-4b.md)
- [Qwen3-Omni-30B-A3B-Instruct vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/qwen3-omni-30b-a3b-instruct-vs-wevisone-vl-4b.md)
- [Qwen3-VL-2B-Instruct vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/qwen3-vl-2b-instruct-vs-wevisone-vl-4b.md)
- [Qwen3-VL-30B-A3B-Instruct vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/qwen3-vl-30b-a3b-instruct-vs-wevisone-vl-4b.md)
- [Qwen3-VL-32B-Instruct vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/qwen3-vl-32b-instruct-vs-wevisone-vl-4b.md)
- [Qwen3-VL-4B-Instruct vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/qwen3-vl-4b-instruct-vs-wevisone-vl-4b.md)
- [Qwen3-VL-8B-Instruct vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/qwen3-vl-8b-instruct-vs-wevisone-vl-4b.md)
- [Qwopus3.8-27B-Flash-V2 vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/qwopus3-8-27b-flash-v2-vs-wevisone-vl-4b.md)
- [Recursive Flint vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/recursive-flint-vs-wevisone-vl-4b.md)
- [Ripple-65B Preview vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/ripple-65b-preview-vs-wevisone-vl-4b.md)
- [SenseNova-Loop-9B-Preview vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/sensenova-loop-9b-preview-vs-wevisone-vl-4b.md)
- [SmolLM3-3B vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/smollm3-3b-vs-wevisone-vl-4b.md)
- [Spark-X2.6-4B vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/spark-x2-6-4b-vs-wevisone-vl-4b.md)
- [Step 3.7 Flash vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/step-3-7-flash-vs-wevisone-vl-4b.md)
- [Swift 1.5 Qwen3.8-27B vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/swift-1-5-qwen3-8-27b-vs-wevisone-vl-4b.md)
- [Swift 1.5 Qwen3.8-Flash-Next vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/swift-1-5-qwen3-8-flash-next-vs-wevisone-vl-4b.md)
- [ThinkingCap (Qwen3.8 27B) vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/thinkingcap-qwen3-8-27b-vs-wevisone-vl-4b.md)
- [WeVisOne-VL-2B vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/wevisone-vl-2b-vs-wevisone-vl-4b.md)
- [WeVisOne-VL-4B vs ZAYA1-8B](https://www.anchorterminal.com/compare/wevisone-vl-4b-vs-zaya1-8b.md)
- [Baidu Unlimited-OCR-2 vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/unlimited-ocr-2-vs-wevisone-vl-4b.md)

---

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