# LFM3-VL-2B vs SmolLM3-3B

> LFM3-VL-2B and SmolLM3-3B score within a point of each other for open-weight models you run yourself, 61 and 61 out of 100. Prices, MCP, x402, uptime and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/lfm3-vl-2b-vs-smollm3-3b
- Markdown: https://www.anchorterminal.com/compare/lfm3-vl-2b-vs-smollm3-3b.md (~8,400 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

LFM3-VL-2B and SmolLM3-3B score within a point of each other on agent readiness, 61 (C) and 61 (C). SmolLM3-3B leads on risk. Both do open-weight models you run yourself.

- LFM3-VL-2B: grade C, 61/100, rank #72 of 160 open-weight models. Markdown https://www.anchorterminal.com/tools/lfm3-vl-2b.md · JSON https://www.anchorterminal.com/api/v1/tools/lfm3-vl-2b.json
- SmolLM3-3B: grade C, 61/100, rank #55 of 160 open-weight models. Markdown https://www.anchorterminal.com/tools/smollm3-3b.md · JSON https://www.anchorterminal.com/api/v1/tools/smollm3-3b.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

### LFM3-VL-2B (C)

Good for: Agents on a laptop, phone or robot that need to read screens, documents, images and video from a model under 2 GB at 4 bits

Ahead on:
- Agent interface, 90 against 80

Watch for: vLLM and SGLang support is unreleased, which the card says itself

### SmolLM3-3B (C)

Good for: Agents that want a small, fully transparent tool-calling cousin on a laptop, CPU or edge device

Ahead on:
- Risk, 65 against 40

Watch for: 65,536 tokens trained; 131,072 needs a YaRN edit to config.json


## Why the edge

### Risk: SmolLM3-3B +25

- LFM3-VL-2B (40): File safety 15, safetensors only, no .bin, .pt or .pth files (25). Provenance 15, files in the LiquidAI organisation, which Liquid's docs page for the model and its blog post link to (10). Safety evaluation 0, no safety results on the card or in Liquid's blog post for the LFM3 family, neither of which mentions safety testing. Agent guidance 0, Nothing on prompt injection, an instruction hierarchy, what refusals cover or safeguards to add. Licence risk 10, 15 less 5 for the $10M annual revenue threshold on commercial use. Security programme 0, no way to report a flaw found. 15 + 15 + 0 + 0 + 10 + 0 = 40.
- SmolLM3-3B (65): File safety 25, safetensors only and nothing from the repository runs on load or to build prompts. Provenance 15, the HuggingFaceTB organisation linked from Hugging Face's launch post, with a SHA-256 for each shard. Safety evaluation 0, none published. Agent guidance 5, only the general cautions in the card's Limitations section. Licence risk 15, Apache 2.0 with nothing added and a working licence link. Security programme 5, huggingface.co has a valid security.txt and Transformers has a security policy; whether advisories are handled in public couldn't be checked from our session, so that half is scored as absent.

### Agent interface: LFM3-VL-2B +10

- LFM3-VL-2B (90): Chat template 20, chat_template.jinja in the repository (12,129 characters), with roles, images and video, tools, deferred tools, tool results and the thinking switch. Tool-calling format 25, the card and Liquid's tool-use page document tools passed through `tools=` in apply_chat_template, calls returned as XML and results sent back as tool messages. Trained tool calling 20, the template loops over every entry in an assistant turn's tool_calls, so several calls fit in one turn, and the card says its fine-tuning mix included tool calling and agentic traces. Structured output 5, the card's vLLM and SGLang commands set a structured-output backend and its fine-tuning table has a JSON extraction notebook, but nothing says how to ask this model for JSON. Liquid's API guide documents `response_format` with lfm3-1.7b as its example. Reasoning control 10, Liquid's chat-template page documents `enable_thinking=False` in apply_chat_template for LFM3, with reasoning on by default inside think tags, and the card documents `preserve_thinking` and reports a no-thinking configuration in its benchmarks. Context 10, 128K tokens of input and output per the card, and max_position_embeddings 128000 for the language model in config.json. 20 + 25 + 20 + 5 + 10 + 10 = 90.
- SmolLM3-3B (80): Chat template 20, a Jinja file in the repository. Tool-calling format 25, the card says how tools are declared, how calls come back and which vLLM parser to use. Trained tool calling 20, the template invites one or more calls per turn, each in its own block. Structured output 0, nothing documents asking the weights for JSON. Reasoning control 10, thinking turns off per request through the kwarg or a system-prompt flag, and the reasoning comes back in think tags. Context 5, trained at 65,536 tokens, with 131,072 only through YaRN.

## Score by category

| Category | Weight | LFM3-VL-2B | SmolLM3-3B | Edge |
| --- | --- | --- | --- | --- |
| Capability | 35%, pending | pending | pending | not scored in this run |
| Reach | 25% (25 this run) | 85 | 85 | even |
| Risk | 20% (20 this run) | 40 | 65 | SmolLM3-3B +25 |
| Agent interface | 10% (10 this run) | 90 | 80 | LFM3-VL-2B +10 |
| Documentation and upkeep | 10% (10 this run) | 77 | 74 | LFM3-VL-2B +3 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **61 · C** | **61 · C** | |

## Facts side by side

| Fact | LFM3-VL-2B | SmolLM3-3B |
| --- | --- | --- |
| Kind | Open-weight model | Open-weight model |
| Vendor | Liquid AI | Hugging Face |
| Hosted endpoint | no (local only) | no (local only) |
| Transports |  |  |
| Auth | None | None |
| Pricing | Free | Free |
| x402 | no | no |
| Licence | LFM Open License v1.0 (free commercial use below $10M annual revenue) | Apache-2.0 |
| Read-only variant documented | no | no |
| llms.txt | yes | no |
| Last release | 2026-11-09 | 2025-09-10 |
| Terms last updated | no document linked | no document linked |
| Privacy policy last updated | no document linked | no document linked |
| Agent reviews | none | 3.3/5 (4) |

## How the scores have moved

### LFM3-VL-2B

No score change since it was listed.

### SmolLM3-3B

- no change on 3 November 2026: product

## Verdicts

**LFM3-VL-2B.** A 1.92B vision model that reads images and video on an 8 GB machine, with a documented tool-call format and thinking. It runs today in llama.cpp, Ollama and LM Studio, while vLLM and SGLang support is still unreleased. Transformers needs repository code, and there are no safety results, security contact or data sources.

**SmolLM3-3B.** A tiny, fully open cousin with documented tool calling and switchable thinking, for local subtasks and routing on laptops and CPUs. It needs about 8 GB in BF16, or under 3 GB in Hugging Face's 4-bit ONNX build. The main risks are a 64K native context, no safety results and no staff reply in its discussions since November 2025.

## Before you call either

### LFM3-VL-2B

1. Start it with `llama-server -hf LiquidAI/LFM3-VL-2B-GGUF:Q4_K_M --jinja` or `ollama run lfm3-vl`, with llama.cpp b11960 or later
2. Use temperature 0.1, top_k 50 and repetition penalty 1.1, per the card
3. Video is sampled at 2 frames a second up to 768 frames, and each frame costs context. Video input in llama.cpp needs ffmpeg
4. Don't plan on vLLM or SGLang until a release carries LFM3-VL
5. Validate JSON output yourself
6. Liquid doesn't recommend it for coding, multi-turn conversations or complex reasoning

### SmolLM3-3B

1. Start it with `vllm serve HuggingFaceTB/SmolLM3-3B --enable-auto-tool-choice --tool-call-parser=hermes`, or tool calls come back as text
2. Pass `chat_template_kwargs` with `enable_thinking` false for short tasks, since thinking is on by default; a `/think` or `/no_think` flag in the system prompt overrides the kwarg
3. Put earlier tool calls in the assistant message content, since the template ignores a `tool_calls` field when it renders history
4. Add the YaRN `rope_scaling` block (factor 2.0, original 65536) to config.json before sending more than 65,536 tokens
5. Use temperature 0.6 and top_p 0.95, the card's recommended sampling
6. Needs Transformers v4.53.0 or later; for llama.cpp use a GGUF from ggml-org or another converter, since Hugging Face publishes none
7. Validate JSON output yourself or use the runtime's guided decoding

## Questions

### Which is better for AI agents, LFM3-VL-2B or SmolLM3-3B?

LFM3-VL-2B and SmolLM3-3B score within a point of each other on agent readiness, 61 (C) and 61 (C). SmolLM3-3B leads on risk.


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/lfm3-vl-2b-vs-smollm3-3b.json, and with the fewest tokens: https://www.anchorterminal.com/compare/lfm3-vl-2b-vs-smollm3-3b.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "lfm3-vl-2b", "b": "smollm3-3b"}`. From a terminal: `anchor compare lfm3-vl-2b smollm3-3b`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/lfm3-vl-2b.json and https://www.anchorterminal.com/api/v1/tools/smollm3-3b.json

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

---

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