# Granite 4.2 30B vs LBS-27B

> Granite 4.2 30B 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/granite-4-2-30b-vs-lbs-27b
- Markdown: https://www.anchorterminal.com/compare/granite-4-2-30b-vs-lbs-27b.md (~9,350 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

Granite 4.2 30B scores 61 (C) on agent readiness against LBS-27B's 55.8 (C), and leads in every scored category. Both do open-weight models you run yourself.

- Granite 4.2 30B: grade C, 61/100, rank #65 of 160 open-weight models. Markdown https://www.anchorterminal.com/tools/granite-4-2-30b.md · JSON https://www.anchorterminal.com/api/v1/tools/granite-4-2-30b.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

### Granite 4.2 30B (C)

Good for: Agents that want a documented, signed, Apache 2.0 reasoning model with tool calling on a 24 GB card

Ahead on:
- Reach, 90 against 60
- Risk, 55 against 50
- Agent interface, 85 against 70
- Documentation and upkeep, 87 against 43

Watch for: No safety results published for it

### 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


## Why the edge

### Documentation and upkeep: Granite 4.2 30B +44

- Granite 4.2 30B (87): Model card 17, Intended use (best for), limitations (ethical considerations and limitations), architecture, parameters (30B), context length (128K native) and 12 tested languages are on the card. Training data 20, IBM's disclosure file for the 30B lists the datasets used in pre-training and post-training as machine-readable metadata, and the card describes the three training stages. Last change 15, the last commit to the repository was on 4 September 2026, 67 days before this check. Responsiveness 20, Of the 4 discussions that aren't pull requests (28 August to 3 November 2026), 3 have a reply from an ibm-granite member. Version policy 5, Granite 4.1 30B stays in its own repository and 4.2 came out in new ones. File health 10, Config, template and card agree on the architecture, the 131,072-token context and the thinking switch. 17 + 20 + 15 + 20 + 5 + 10 = 87.
- 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.

### Reach: Granite 4.2 30B +30

- Granite 4.2 30B (90): Memory 25, IBM's own 4-bit MLX build granite-4.2-30b-q4-mlx is 16.47 GB, and 16.47 GB × 1.2 = 19.8 GB, which fits 24 GB but not 16 GB. Its Q4_0 GGUF is 16.58 GB and Ollama's library build granite4.2:30b 18 GB, the same band. Runtimes 25, Released versions run the granite architecture in llama.cpp (granite, b12242), vLLM (GraniteForCausalLM in the v0.33.0 registry), SGLang (granite.py at v0.5.23), Transformers (v5.22.2) and Ollama (its own granite4.2 library entry, 30b tag). Builds 15, IBM publishes FP8, MXFP4 and NVFP4 safetensors builds, a GGUF repository with Q4_0 to Q8_0 and BF16 files, and 4-bit, 8-bit and BF16 MLX builds, so quantised builds at two precisions or more. Terms 15, Apache 2.0, an OSI-approved licence, with no use policy or other terms added on the card. Download 10, the Hub API reports gated false for the BF16, FP8, MXFP4, NVFP4, GGUF and MLX repositories, so the files download with no account and nothing to accept. Hosted 0, Hugging Face maps one inference provider (DeepInfra, live), short of the two the line needs. 25 + 25 + 15 + 15 + 10 + 0 = 90.
- 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.

### Agent interface: Granite 4.2 30B +15

- Granite 4.2 30B (85): Chat template 20, chat_template.jinja in the repository, with roles, tools, tool responses, the thinking switch and low effort. Tool-calling format 25, the card has tool-calling sections for vLLM and SGLang, declares tools with OpenAI's function schema and names the parser to use, qwen3_coder, which both runtimes ship in the released versions read. Trained tool calling 20, the template loops over every entry in an assistant turn's tool_calls, so it renders several calls in one turn, and the card names tool calling and agentic workflows as what it's best for. Structured output 0, the card doesn't document JSON or JSON Schema output or how to ask for it. Reasoning control 10, the card documents thinking on by default, non-thinking and low-effort modes per request through the template (enable_thinking and low_effort), with the reasoning returned apart from the answer. Context 10, 131,072 tokens natively per the card and config.json. 20 + 25 + 20 + 0 + 10 + 10 = 85.
- 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.

### Risk: Granite 4.2 30B +5

- Granite 4.2 30B (55): File safety 15, safetensors only, no .bin, .pt or .pth files (25). Provenance 15, the files sit in the ibm-granite organisation, which IBM's Granite docs and the GitHub README link to (10). Safety evaluation 0, no safety results on the card. Agent guidance 5, General cautions. Licence risk 15, Apache 2.0 has no use policy, field-of-use limit, threshold or change clause, and the card's licence link resolves. Security programme 5, www.ibm.com/.well-known/security.txt names IBM PSIRT, read for the 3B listing on 4 November 2026 (5). 15 + 15 + 0 + 5 + 15 + 5 = 55.
- 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 | Granite 4.2 30B | LBS-27B | Edge |
| --- | --- | --- | --- | --- |
| Capability | 35%, pending | pending | pending | not scored in this run |
| Reach | 25% (25 this run) | 90 | 60 | Granite 4.2 30B +30 |
| Risk | 20% (20 this run) | 55 | 50 | Granite 4.2 30B +5 |
| Agent interface | 10% (10 this run) | 85 | 70 | Granite 4.2 30B +15 |
| Documentation and upkeep | 10% (10 this run) | 87 | 43 | Granite 4.2 30B +44 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **61 · C** | **55.8 · C** | |

## Facts side by side

| Fact | Granite 4.2 30B | LBS-27B |
| --- | --- | --- |
| Kind | Open-weight model | Open-weight model |
| Vendor | IBM | inclusionAI (Ant Group) |
| Hosted endpoint | no (local only) | no (local only) |
| Transports |  |  |
| Auth | None | None |
| Pricing | Free | Free |
| x402 | no | no |
| Licence | 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 | 2026-09-04 | 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

### Granite 4.2 30B

No score change since it was listed.

### LBS-27B

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

## Verdicts

**Granite 4.2 30B.** IBM's largest reasoning cousin, with the same strengths as the 3B. It runs in every runtime we count from IBM's own builds on a 24 GB card, is signed, plain Apache 2.0, and comes with a disclosure of its training data. No safety results are published and structured output isn't documented.

**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

### Granite 4.2 30B

1. Start it with `ollama run granite4.2:30b`, or `llama-server -hf ibm-granite/granite-4.2-30b-GGUF:Q4_K_M --jinja`
2. With vLLM 0.32.0 or later leave out `--reasoning-parser-plugin`, since the parser is built in, and use `--tool-call-parser qwen3_coder`
3. Thinking is on by default. Pass `enable_thinking` false to turn it off or `low_effort` true for short reasoning
4. The context is 131,072 tokens. The card's 512K extension isn't documented
5. Validate JSON output yourself, since structured output isn't documented
6. IBM recommends Granite Guardian beside it to flag risky inputs and outputs

### 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, Granite 4.2 30B or LBS-27B?

Granite 4.2 30B scores 61 (C) on agent readiness against LBS-27B's 55.8 (C), and leads in every scored category.


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/granite-4-2-30b-vs-lbs-27b.json, and with the fewest tokens: https://www.anchorterminal.com/compare/granite-4-2-30b-vs-lbs-27b.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "granite-4-2-30b", "b": "lbs-27b"}`. From a terminal: `anchor compare granite-4-2-30b lbs-27b`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/granite-4-2-30b.json and https://www.anchorterminal.com/api/v1/tools/lbs-27b.json

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- [Granite 4.2 30B vs MiniCPM5-2B](https://www.anchorterminal.com/compare/granite-4-2-30b-vs-minicpm5-2b.md)
- [Granite 4.2 30B vs MiniMax-M2.5](https://www.anchorterminal.com/compare/granite-4-2-30b-vs-minimax-m2-5.md)
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- [Granite 4.2 30B vs Mistral Large 4](https://www.anchorterminal.com/compare/granite-4-2-30b-vs-mistral-large-4.md)
- [Granite 4.2 30B vs Muse Glimmer 30B](https://www.anchorterminal.com/compare/granite-4-2-30b-vs-muse-glimmer-30b.md)
- [Granite 4.2 30B vs Nanbeige4.2-3B](https://www.anchorterminal.com/compare/granite-4-2-30b-vs-nanbeige-4-2-3b.md)
- [Granite 4.2 30B vs Nanbeige4.3-33B](https://www.anchorterminal.com/compare/granite-4-2-30b-vs-nanbeige-4-3-33b.md)
- [Granite 4.2 30B vs NVIDIA Nemotron 3.5 Bolt E4B 4GB](https://www.anchorterminal.com/compare/granite-4-2-30b-vs-nemotron-3-5-bolt-e4b-4gb.md)
- [Granite 4.2 30B vs Nemotron 3.5 Lightning 30B A3B](https://www.anchorterminal.com/compare/granite-4-2-30b-vs-nemotron-3-5-lightning-30b-a3b.md)
- [Granite 4.2 30B vs Nemotron 3 Nano 30B A3B](https://www.anchorterminal.com/compare/granite-4-2-30b-vs-nemotron-3-nano-30b-a3b.md)
- [Granite 4.2 30B vs Nemotron 3 Nano 4B](https://www.anchorterminal.com/compare/granite-4-2-30b-vs-nemotron-3-nano-4b.md)
- [Granite 4.2 30B vs Nemotron 3 Nano Omni 30B A3B Reasoning](https://www.anchorterminal.com/compare/granite-4-2-30b-vs-nemotron-3-nano-omni-30b-a3b-reasoning.md)
- [Granite 4.2 30B vs Nemotron 3 Super 120B A12B](https://www.anchorterminal.com/compare/granite-4-2-30b-vs-nemotron-3-super-120b-a12b.md)
- [Granite 4.2 30B vs Nemotron 3 Ultra 550B A55B](https://www.anchorterminal.com/compare/granite-4-2-30b-vs-nemotron-3-ultra-550b-a55b.md)
- [Granite 4.2 30B vs North Mini Code 1.0](https://www.anchorterminal.com/compare/granite-4-2-30b-vs-north-mini-code-1-0.md)
- [Granite 4.2 30B vs occamy-1.0](https://www.anchorterminal.com/compare/granite-4-2-30b-vs-occamy-1-0.md)
- [Granite 4.2 30B vs Olmo 3 7B Think](https://www.anchorterminal.com/compare/granite-4-2-30b-vs-olmo-3-7b-think.md)
- [Granite 4.2 30B vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/granite-4-2-30b-vs-ornith-1-5-122b.md)
- [Granite 4.2 30B vs Ornith-1.5-35B-A3B](https://www.anchorterminal.com/compare/granite-4-2-30b-vs-ornith-1-5-35b-a3b.md)
- [Granite 4.2 30B vs Ornith-1.5-397B](https://www.anchorterminal.com/compare/granite-4-2-30b-vs-ornith-1-5-397b.md)
- [Granite 4.2 30B vs Ornith-1.5-9B](https://www.anchorterminal.com/compare/granite-4-2-30b-vs-ornith-1-5-9b.md)
- [Granite 4.2 30B vs OTel-2.0-LLM-31B-IT](https://www.anchorterminal.com/compare/granite-4-2-30b-vs-otel-2-0-llm-31b-it.md)
- [Granite 4.2 30B vs Qwen-AgentWorld-35B-A3B](https://www.anchorterminal.com/compare/granite-4-2-30b-vs-qwen-agentworld-35b-a3b.md)
- [Granite 4.2 30B vs Qwen3-30B-A3B-Instruct-2507](https://www.anchorterminal.com/compare/granite-4-2-30b-vs-qwen3-30b-a3b-instruct-2507.md)
- [Granite 4.2 30B vs Qwen3-4B-Instruct-2507](https://www.anchorterminal.com/compare/granite-4-2-30b-vs-qwen3-4b-instruct-2507.md)
- [Granite 4.2 30B vs Qwen3.5-0.8B](https://www.anchorterminal.com/compare/granite-4-2-30b-vs-qwen3-5-0-8b.md)
- [Granite 4.2 30B vs Qwen3.5-122B-A10B](https://www.anchorterminal.com/compare/granite-4-2-30b-vs-qwen3-5-122b-a10b.md)
- [Granite 4.2 30B vs Qwen3.5-2B](https://www.anchorterminal.com/compare/granite-4-2-30b-vs-qwen3-5-2b.md)
- [Granite 4.2 30B vs Qwen3.5-397B-A17B](https://www.anchorterminal.com/compare/granite-4-2-30b-vs-qwen3-5-397b-a17b.md)
- [Granite 4.2 30B vs Qwen3.5-4B](https://www.anchorterminal.com/compare/granite-4-2-30b-vs-qwen3-5-4b.md)
- [Granite 4.2 30B vs Qwen3.5-9B](https://www.anchorterminal.com/compare/granite-4-2-30b-vs-qwen3-5-9b.md)
- [Granite 4.2 30B vs Qwen3.6-27B](https://www.anchorterminal.com/compare/granite-4-2-30b-vs-qwen3-6-27b.md)
- [Granite 4.2 30B vs Qwen3.6-35B-A3B](https://www.anchorterminal.com/compare/granite-4-2-30b-vs-qwen3-6-35b-a3b.md)
- [Granite 4.2 30B vs Qwen3.8-27B](https://www.anchorterminal.com/compare/granite-4-2-30b-vs-qwen3-8-27b.md)
- [Granite 4.2 30B vs Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/granite-4-2-30b-vs-qwen3-8-flash-next.md)
- [Granite 4.2 30B vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/granite-4-2-30b-vs-qwen3-coder-30b-a3b-instruct.md)
- [Granite 4.2 30B vs Qwen3-Coder-Next](https://www.anchorterminal.com/compare/granite-4-2-30b-vs-qwen3-coder-next.md)
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- [Granite 4.2 30B vs Qwen3-VL-2B-Instruct](https://www.anchorterminal.com/compare/granite-4-2-30b-vs-qwen3-vl-2b-instruct.md)
- [Granite 4.2 30B vs Qwen3-VL-30B-A3B-Instruct](https://www.anchorterminal.com/compare/granite-4-2-30b-vs-qwen3-vl-30b-a3b-instruct.md)
- [Granite 4.2 30B vs Qwen3-VL-32B-Instruct](https://www.anchorterminal.com/compare/granite-4-2-30b-vs-qwen3-vl-32b-instruct.md)
- [Granite 4.2 30B vs Qwen3-VL-4B-Instruct](https://www.anchorterminal.com/compare/granite-4-2-30b-vs-qwen3-vl-4b-instruct.md)
- [Granite 4.2 30B vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/granite-4-2-30b-vs-qwen3-vl-8b-instruct.md)
- [Granite 4.2 30B vs Qwopus3.8-27B-Flash-V2](https://www.anchorterminal.com/compare/granite-4-2-30b-vs-qwopus3-8-27b-flash-v2.md)
- [Granite 4.2 30B vs Recursive Flint](https://www.anchorterminal.com/compare/granite-4-2-30b-vs-recursive-flint.md)
- [Granite 4.2 30B vs Ripple-65B Preview](https://www.anchorterminal.com/compare/granite-4-2-30b-vs-ripple-65b-preview.md)
- [Granite 4.2 30B vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/granite-4-2-30b-vs-sensenova-loop-9b-preview.md)
- [Granite 4.2 30B vs SmolLM3-3B](https://www.anchorterminal.com/compare/granite-4-2-30b-vs-smollm3-3b.md)
- [Granite 4.2 30B vs Spark-X2.6-4B](https://www.anchorterminal.com/compare/granite-4-2-30b-vs-spark-x2-6-4b.md)
- [Granite 4.2 30B vs Step 3.7 Flash](https://www.anchorterminal.com/compare/granite-4-2-30b-vs-step-3-7-flash.md)
- [Granite 4.2 30B vs Swift 1.5 Qwen3.8-27B](https://www.anchorterminal.com/compare/granite-4-2-30b-vs-swift-1-5-qwen3-8-27b.md)
- [Granite 4.2 30B vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/granite-4-2-30b-vs-swift-1-5-qwen3-8-flash-next.md)
- [Granite 4.2 30B vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/granite-4-2-30b-vs-thinkingcap-qwen3-8-27b.md)
- [Granite 4.2 30B vs Baidu Unlimited-OCR-2](https://www.anchorterminal.com/compare/granite-4-2-30b-vs-unlimited-ocr-2.md)
- [Granite 4.2 30B vs WeVisOne-VL-2B](https://www.anchorterminal.com/compare/granite-4-2-30b-vs-wevisone-vl-2b.md)
- [Granite 4.2 30B vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/granite-4-2-30b-vs-wevisone-vl-4b.md)
- [Granite 4.2 30B vs ZAYA1-8B](https://www.anchorterminal.com/compare/granite-4-2-30b-vs-zaya1-8b.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)
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- [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)
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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)
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- [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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