# Cola2 vs LBS-27B

> LBS-27B scores 55.8 (C) to Cola2's 33.9 (F) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/cola2-vs-lbs-27b
- Markdown: https://www.anchorterminal.com/compare/cola2-vs-lbs-27b.md (~8,500 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

LBS-27B scores 55.8 (C) on agent readiness against Cola2's 33.9 (F), and leads in 3 of 4 scored categories. Cola2 leads on documentation and upkeep. Both do open-weight models you run yourself.

- Cola2: grade F, 33.9/100, rank #160 of 160 open-weight models. Markdown https://www.anchorterminal.com/tools/cola2.md · JSON https://www.anchorterminal.com/api/v1/tools/cola2.json
- 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
- 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

### Cola2 (F)

Good for: Researchers working on latent or diffusion language models who want a checkpoint to study

Ahead on:
- Documentation and upkeep, 58 against 43

Watch for: No licence stated for the weights

### 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.

Ahead on:
- Reach, 60 against 25
- Risk, 50 against 40
- Agent interface, 70 against 20

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


## Why the edge

### Agent interface: LBS-27B +50

- Cola2 (20): Chat template 20, A chat template in tokenizer_config.json (4,116 characters), which came with the Qwen3 tokenizer. Tool-calling format 0, none. Trained tool calling 0, not trained for tool calling. Structured output 0, Nothing about JSON or schema-constrained output. Reasoning control 0, no reasoning mode. Context 0, no context length is stated. 20 + 0 + 0 + 0 + 0 + 0 = 20.
- LBS-27B (70): The chat template earns 20, Qwen's Jinja file in the repository. The tool-calling format earns 10, as general tool calls rest on the inherited template and the crop action is parsed by inclusionAI's own code, not a runtime parser. Trained tool calling earns 20 for up to two crop actions per turn learned in GRPO. Structured output earns 0. Reasoning control earns 10, with reasoning effort documented and the reasoning shown as think text. Context earns 10 for 262,144 tokens with no scaling.

### Reach: LBS-27B +35

- Cola2 (25): Memory 15, the only build is the F32 safetensors set, 35.07 GB, and 35.07 GB × 1.2 = 42.1 GB, within 64 GB. Loaded as BF16, as the card's example does, it needs about half, but the line reads the file size. Runtimes 0, none of the six runs it in a released version. Builds 0, one set of weights and no quantised build. Terms 0, no licence for the weights. 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, and nothing names an API that serves it. 15 + 0 + 0 + 0 + 10 + 0 = 25.
- 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.

### Documentation and upkeep: Cola2 +15

- Cola2 (58): Model card 8, Intended use and limitations (the out-of-scope list, and the unconverged latent model) and the architecture are on the card and the GitHub model card it links. Training data 15, the GitHub model card names the source (OLMo 2 pretraining text, retokenised) and the mix by stage with token counts, 346.03B in all. Last change 20, All six commits are from 6 November 2026, four days before this check, the last one updating a checksum in the README. Responsiveness 0, no discussions on the repository, so nobody has asked anything yet and the line reads as none answered, as settled in calibration. Version policy 5, A first release. File health 10, Config, files and card agree: F32 weights, a float32 config and a card that says to load them as bfloat16, with SHA256SUMS to check the download. 8 + 15 + 20 + 0 + 5 + 10 = 58.
- 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.

### Risk: LBS-27B +10

- Cola2 (40): File safety 15, safetensors only, no .bin, .pt or .pth files (25). Provenance 15, the files sit in the ByteDance-Seed organisation, which the ByteDance-Seed GitHub repository for the model links to (10). Safety evaluation 0, no safety results. Agent guidance 5, General cautions in the GitHub model card: not instruction-tuned or safety-aligned, not for use as an assistant, for facts or advice, or for high-impact decisions about people. Licence risk 0, With no licence for the weights there is nothing to hold ByteDance to. Security programme 5, the GitHub repository's SECURITY.md sends reports to ByteDance's security centre and says how they're assessed (5). 15 + 15 + 0 + 5 + 0 + 5 = 40.
- 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.

## Score by category

| Category | Weight | Cola2 | LBS-27B | Edge |
| --- | --- | --- | --- | --- |
| Capability | 35%, pending | pending | pending | not scored in this run |
| Reach | 25% (25 this run) | 25 | 60 | LBS-27B +35 |
| Risk | 20% (20 this run) | 40 | 50 | LBS-27B +10 |
| Agent interface | 10% (10 this run) | 20 | 70 | LBS-27B +50 |
| Documentation and upkeep | 10% (10 this run) | 58 | 43 | Cola2 +15 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **33.9 · F** | **55.8 · C** | |

## Facts side by side

| Fact | Cola2 | LBS-27B |
| --- | --- | --- |
| Kind | Open-weight model | Open-weight model |
| Vendor | ByteDance (Seed) | inclusionAI (Ant Group) |
| Hosted endpoint | no (local only) | no (local only) |
| Transports |  |  |
| Auth | None | None |
| Pricing | Free | Free |
| x402 | no | no |
| Licence | None stated for the weights (the code is Apache 2.0) | 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) |
| Read-only variant documented | no | no |
| llms.txt | no | no |
| Last release | 2026-11-06 | 2026-10-26 |
| Terms last updated | no document linked | no document linked |
| Privacy policy last updated | no document linked | no document linked |

## How the scores have moved

### Cola2

No score change since it was listed.

### LBS-27B

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

## Verdicts

**Cola2.** A research release, and an honest one: ByteDance Seed says it's a base model with an unconverged latent stage, scoring below Llama-3-8B on its own table. It's here for people studying continuous-latent generation. Agents can't use it as a model: 32-token completions, no chat or tools, the repository's own code to load it, and no licence on the weights.

**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.

## Before you call either

### Cola2

1. Don't plan to use this as your model. It completes short prompts and wasn't tuned to follow instructions
2. Don't use it commercially on the strength of this listing. The weights have no stated licence
3. If you study it, read modeling_cola2.py first: trust_remote_code runs it
4. Pin Transformers below 5, as the card requires
5. Pass a seeded torch.Generator to generate(). Output varies between runs even with greedy decoding
6. Check the download with `sha256sum -c SHA256SUMS`

### 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

## Questions

### Which is better for AI agents, Cola2 or LBS-27B?

LBS-27B scores 55.8 (C) on agent readiness against Cola2's 33.9 (F), and leads in 3 of 4 scored categories. Cola2 leads on documentation and upkeep.


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/cola2-vs-lbs-27b.json, and with the fewest tokens: https://www.anchorterminal.com/compare/cola2-vs-lbs-27b.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "cola2", "b": "lbs-27b"}`. From a terminal: `anchor compare cola2 lbs-27b`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/cola2.json and https://www.anchorterminal.com/api/v1/tools/lbs-27b.json

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- [Cola2 vs Qwen3-VL-30B-A3B-Instruct](https://www.anchorterminal.com/compare/cola2-vs-qwen3-vl-30b-a3b-instruct.md)
- [Cola2 vs Qwen3-VL-32B-Instruct](https://www.anchorterminal.com/compare/cola2-vs-qwen3-vl-32b-instruct.md)
- [Cola2 vs Qwen3-VL-4B-Instruct](https://www.anchorterminal.com/compare/cola2-vs-qwen3-vl-4b-instruct.md)
- [Cola2 vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/cola2-vs-qwen3-vl-8b-instruct.md)
- [Cola2 vs Qwopus3.8-27B-Flash-V2](https://www.anchorterminal.com/compare/cola2-vs-qwopus3-8-27b-flash-v2.md)
- [Cola2 vs Recursive Flint](https://www.anchorterminal.com/compare/cola2-vs-recursive-flint.md)
- [Cola2 vs Ripple-65B Preview](https://www.anchorterminal.com/compare/cola2-vs-ripple-65b-preview.md)
- [Cola2 vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/cola2-vs-sensenova-loop-9b-preview.md)
- [Cola2 vs SmolLM3-3B](https://www.anchorterminal.com/compare/cola2-vs-smollm3-3b.md)
- [Cola2 vs Spark-X2.6-4B](https://www.anchorterminal.com/compare/cola2-vs-spark-x2-6-4b.md)
- [Cola2 vs Step 3.7 Flash](https://www.anchorterminal.com/compare/cola2-vs-step-3-7-flash.md)
- [Cola2 vs Swift 1.5 Qwen3.8-27B](https://www.anchorterminal.com/compare/cola2-vs-swift-1-5-qwen3-8-27b.md)
- [Cola2 vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/cola2-vs-swift-1-5-qwen3-8-flash-next.md)
- [Cola2 vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/cola2-vs-thinkingcap-qwen3-8-27b.md)
- [Cola2 vs Baidu Unlimited-OCR-2](https://www.anchorterminal.com/compare/cola2-vs-unlimited-ocr-2.md)
- [Cola2 vs WeVisOne-VL-2B](https://www.anchorterminal.com/compare/cola2-vs-wevisone-vl-2b.md)
- [Cola2 vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/cola2-vs-wevisone-vl-4b.md)
- [Cola2 vs ZAYA1-8B](https://www.anchorterminal.com/compare/cola2-vs-zaya1-8b.md)
- [Cosmos-Reason2-2B vs LBS-27B](https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-lbs-27b.md)
- [Darwin-36B-Opus vs LBS-27B](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-lbs-27b.md)
- [DeepSeek-V3.2 vs LBS-27B](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-lbs-27b.md)
- [DeepSeek V4.1 Flash vs LBS-27B](https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-lbs-27b.md)
- [DeepSeek-V4-Flash-0731 vs LBS-27B](https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-lbs-27b.md)
- [Devstral Small 2 vs LBS-27B](https://www.anchorterminal.com/compare/devstral-small-2-vs-lbs-27b.md)
- [DiffusionGemma 26B A4B IT vs LBS-27B](https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-lbs-27b.md)
- [EXAONE 4.5 33B vs LBS-27B](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-lbs-27b.md)
- [Gemma 4 12B IT vs LBS-27B](https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-lbs-27b.md)
- [Gemma 4 26B A4B IT vs LBS-27B](https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-lbs-27b.md)
- [Gemma 4 31B IT vs LBS-27B](https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-lbs-27b.md)
- [Gemma 4 E2B IT vs LBS-27B](https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-lbs-27b.md)
- [Gemma 4 E4B IT vs LBS-27B](https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-lbs-27b.md)
- [GLM-4.5-Air vs LBS-27B](https://www.anchorterminal.com/compare/glm-4-5-air-vs-lbs-27b.md)
- [GLM-4.7-Flash vs LBS-27B](https://www.anchorterminal.com/compare/glm-4-7-flash-vs-lbs-27b.md)
- [GLM-5.3-Flash vs LBS-27B](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-lbs-27b.md)
- [GLM-5.3 vs LBS-27B](https://www.anchorterminal.com/compare/glm-5-3-vs-lbs-27b.md)
- [gpt-oss-120b vs LBS-27B](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-lbs-27b.md)
- [gpt-oss-20b vs LBS-27B](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-lbs-27b.md)
- [Granite 4.2 30B vs LBS-27B](https://www.anchorterminal.com/compare/granite-4-2-30b-vs-lbs-27b.md)
- [Granite 4.2 3B vs LBS-27B](https://www.anchorterminal.com/compare/granite-4-2-3b-vs-lbs-27b.md)
- [Granite 4.2 8B vs LBS-27B](https://www.anchorterminal.com/compare/granite-4-2-8b-vs-lbs-27b.md)
- [Hy-Memory-30B-A3B vs LBS-27B](https://www.anchorterminal.com/compare/hy-memory-30b-a3b-vs-lbs-27b.md)
- [Hy3 vs LBS-27B](https://www.anchorterminal.com/compare/hy3-vs-lbs-27b.md)
- [Inkling-Small vs LBS-27B](https://www.anchorterminal.com/compare/inkling-small-vs-lbs-27b.md)
- [Inkling vs LBS-27B](https://www.anchorterminal.com/compare/inkling-vs-lbs-27b.md)
- [InternVL3.5-GPT-OSS-20B-A4B-Preview vs LBS-27B](https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-lbs-27b.md)
- [Kimi K3.1 Pro vs LBS-27B](https://www.anchorterminal.com/compare/kimi-k3-1-pro-vs-lbs-27b.md)
- [Kimi K3 vs LBS-27B](https://www.anchorterminal.com/compare/kimi-k3-vs-lbs-27b.md)
- [Kolibri-1 vs LBS-27B](https://www.anchorterminal.com/compare/kolibri-1-vs-lbs-27b.md)
- [Kronos vs LBS-27B](https://www.anchorterminal.com/compare/kronos-vs-lbs-27b.md)
- [Laguna M.1 vs LBS-27B](https://www.anchorterminal.com/compare/laguna-m-1-vs-lbs-27b.md)
- [Laguna S 2.1 vs LBS-27B](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-lbs-27b.md)
- [Laguna XS 2.1 vs LBS-27B](https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-lbs-27b.md)
- [LBS-27B vs LFM2.5-2.6B](https://www.anchorterminal.com/compare/lbs-27b-vs-lfm2-5-2-6b.md)
- [LBS-27B vs LFM3-1.7B](https://www.anchorterminal.com/compare/lbs-27b-vs-lfm3-1-7b.md)
- [LBS-27B vs LFM3-Audio-2B](https://www.anchorterminal.com/compare/lbs-27b-vs-lfm3-audio-2b.md)
- [LBS-27B vs LFM3-Omni-2B](https://www.anchorterminal.com/compare/lbs-27b-vs-lfm3-omni-2b.md)
- [LBS-27B vs LFM3-VL-2B](https://www.anchorterminal.com/compare/lbs-27b-vs-lfm3-vl-2b.md)
- [LBS-27B vs Ling-3.0-tiny](https://www.anchorterminal.com/compare/lbs-27b-vs-ling-3-0-tiny.md)
- [LBS-27B vs Ling-3.1-flash-1019](https://www.anchorterminal.com/compare/lbs-27b-vs-ling-3-1-flash-1019.md)
- [LBS-27B vs LongCat-2.5](https://www.anchorterminal.com/compare/lbs-27b-vs-longcat-2-5.md)
- [LBS-27B vs MiMo-V2.6 Distill Qwen 9B](https://www.anchorterminal.com/compare/lbs-27b-vs-mimo-v2-6-distill-qwen-9b.md)
- [LBS-27B vs MiMo-V2.6-Flash-RL](https://www.anchorterminal.com/compare/lbs-27b-vs-mimo-v2-6-flash-rl.md)
- [LBS-27B vs MiniCPM-o 4.5](https://www.anchorterminal.com/compare/lbs-27b-vs-minicpm-o-4-5.md)
- [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 WeVisOne-VL-4B](https://www.anchorterminal.com/compare/lbs-27b-vs-wevisone-vl-4b.md)
- [LBS-27B vs ZAYA1-8B](https://www.anchorterminal.com/compare/lbs-27b-vs-zaya1-8b.md)

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