# Inkling 2 Small vs SmolLM3-3B

> SmolLM3-3B scores 61 (C) to Inkling 2 Small's 58.8 (C) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/inkling-2-small-vs-smollm3-3b
- Markdown: https://www.anchorterminal.com/compare/inkling-2-small-vs-smollm3-3b.md (~9,200 tokens)
- Slim: https://www.anchorterminal.com/compare/inkling-2-small-vs-smollm3-3b.min.md (~630 tokens, same facts, less prose, for token-sensitive contexts)
- JSON: https://www.anchorterminal.com/compare/inkling-2-small-vs-smollm3-3b.json (this page as data, same URL with Accept: application/json)
- 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: 2026-11-12

SmolLM3-3B scores 61 (C) on agent readiness against Inkling 2 Small's 58.8 (C), and leads in 2 of 4 scored categories. Inkling 2 Small leads on agent interface. Both do open-weight models you run yourself.

- Inkling 2 Small: grade C, 58.8/100, rank #102 of 161 open-weight models. Markdown https://www.anchorterminal.com/tools/inkling-2-small.md · JSON https://www.anchorterminal.com/api/v1/tools/inkling-2-small.json
- SmolLM3-3B: grade C, 61/100, rank #55 of 161 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 6472 open weights comparisons: https://www.anchorterminal.com/compare/open-weights/index.md

## Which one, for what

### Inkling 2 Small (C)

Good for: Teams with 512 GB or more of datacentre GPU memory who want Thinking Machines' newest open multimodal agent model and can run a runtime's pre-release image.

Ahead on:
- Agent interface, 85 against 80

Watch for: The smaller checkpoint needs about 472 GB, and Thinking Machines says 500 GB of GPU memory

### SmolLM3-3B (C)

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

Ahead on:
- Reach, 85 against 40
- Documentation and upkeep, 74 against 67

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


## Why the edge

### Reach: SmolLM3-3B +45

- Inkling 2 Small (40): Memory 0 of 30, the smallest build is Thinking Machines' NVFP4 checkpoint at 393.5 GB, about 472 GB with a fifth added, above the 256 GB line. Runtimes 0, no released version of the six runs it; vLLM and SGLang serve it from their own images and Transformers has it on its main branch only. Builds 15, two precisions from the publisher (NVFP4 and MXFP8). Terms 10, Apache 2.0 with a binding acceptable use policy on top, read as a custom licence. Download 10, no gate. Hosted 5, Thinking Machines' own Tinker serves it as beta serverless inference, and Together is live on Hugging Face. 0 + 0 + 15 + 10 + 10 + 5 = 40.
- SmolLM3-3B (85): Memory 30, the smallest 4-bit build Hugging Face publishes is its own ONNX q4f16 at 2.1 GB, about 2.5 GB with the fifth added, and the full BF16 files that the counted runtimes load come to about 7.4 GB, both under 16 GB. Runtimes 20, released Transformers carries the model code, llama.cpp knows the architecture, and vLLM and SGLang run it through their Transformers backends in released versions; Ollama has no library entry and LM Studio's catalogue has none, so those two earn nothing. Builds 10, Hugging Face's ONNX repository has 4-bit builds, one of the checklist's kinds, and int8 builds, which are neither FP8 nor GGUF. They run in ONNX Runtime and Transformers.js rather than the runtimes above. Terms 15, plain Apache 2.0, scored by its terms since the repository holds no LICENSE file. Download 10, not gated. Hosted 0, no inference provider is listed for it on the Hub and none of the provider lists checked carries it.

### Documentation and upkeep: SmolLM3-3B +7

- Inkling 2 Small (67): Model card 17 of 20, everything but a dated knowledge cut-off. Training data 15, an EU training-content summary with sources, mix, an October 2026 collection cut-off and filtering. Last change 20, the files were uploaded on 12 November 2026. Responsiveness 0, the repository has no questions yet, which reads as none answered. Version policy 5, a first release. File health 10, the files agree and no broken-file report waits. 17 + 15 + 20 + 0 + 5 + 10 = 67.
- SmolLM3-3B (74): Model card 14, it covers limitations, architecture, parameters, context and languages but has no intended-use section and leaves the June 2025 cut-off to the chat template. Training data 20, the datasets, mixture weights and post-training set are published with sources and sizes. Last change 20, Hugging Face's ONNX build changed its tokenizer config on 28 October 2026, though the main repository hasn't changed since 10 September 2025. Responsiveness 10, staff answered 14 of 36 discussions, none since November 2025. Version policy 5, a first release never replaced, with no dated notes. File health 5, template and tokenizer reports wait with no reply.

### Agent interface: Inkling 2 Small +5

- Inkling 2 Small (85): Chat template 20, a Jinja file in the repository. Tool-calling format 25, Thinking Machines' tml-renderers guide shows how tools are declared and how calls come back for this model, and its package ships the parser. Trained tool calling 20, several calls in one turn. Structured output 0, not documented. Reasoning control 10, thinking effort is set per request from none to xhigh, and the reasoning comes back in reasoning_content. Context 10, up to 1M tokens. 20 + 25 + 20 + 0 + 10 + 10 = 85.
- 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 | Inkling 2 Small | SmolLM3-3B | Edge |
| --- | --- | --- | --- | --- |
| Capability | 35%, pending | pending | pending | not scored in this run |
| Reach | 25% (25 this run) | 40 | 85 | SmolLM3-3B +45 |
| Risk | 20% (20 this run) | 65 | 65 | even |
| Agent interface | 10% (10 this run) | 85 | 80 | Inkling 2 Small +5 |
| Documentation and upkeep | 10% (10 this run) | 67 | 74 | SmolLM3-3B +7 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **58.8 · C** | **61 · C** | |

## Facts side by side

| Fact | Inkling 2 Small | SmolLM3-3B |
| --- | --- | --- |
| Kind | Open-weight model | Open-weight model |
| Vendor | Thinking Machines Lab | Hugging Face |
| 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 |
| Read-only variant documented | no | no |
| llms.txt | no | no |
| Last release | 2026-11-12 | 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

### Inkling 2 Small

- +6.7 on 12 November 2026 (D to C): product

### SmolLM3-3B

- no change on 3 November 2026: product

## Verdicts

**Inkling 2 Small.** Thinking Machines' newest open model, a 594B mixture-of-experts generalist with images in, several tool calls a turn and per-request thinking effort. The NVFP4 checkpoint needs about 472 GB, and no released runtime runs it yet, so today that means vLLM's or SGLang's own images, or Tinker and Together hosted. The use policy binds on download and can change.

**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

### Inkling 2 Small

1. No released runtime runs it yet. Serve the NVFP4 checkpoint from SGLang's dev-inkling-2-small image with the cookbook's recipe for your hardware, or from vLLM's vllm/vllm-openai:inkling-2-small image
2. In vLLM pass `--reasoning-parser inkling --enable-auto-tool-choice --tool-call-parser inkling`. In SGLang the tool-call parser is `inkling2` and the reasoning parser `inkling`
3. Transformers' main branch loads only thinkingmachines/Inkling-2-Small-MXFP8, the 622.8 GB checkpoint, and no release has the code yet
4. Pass `reasoning_effort` as none, minimal, low, medium, high (the default), xhigh or max, or a number from 0 to 0.99
5. Effort none conditions the model toward no reasoning but doesn't forbid it, and higher effort needs a larger max_tokens
6. Tool call arguments must reach the template as an object, not a JSON string, or it raises an error
7. Images should be 40 to 4096 px a side. The model takes no audio, and the template raises an error for an audio part
8. Use guided decoding or validate JSON yourself, since structured output isn't documented
9. Without the hardware, call it on Tinker's OpenAI-compatible endpoint with a Tinker key, at $0.30 input and $1.00 output per million tokens as read on 6 November 2026
10. Read the Model Acceptable Use Policy before deploying, it binds on download and bars some uses that are legal

### 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, Inkling 2 Small or SmolLM3-3B?

SmolLM3-3B scores 61 (C) on agent readiness against Inkling 2 Small's 58.8 (C), and leads in 2 of 4 scored categories. Inkling 2 Small leads on agent interface.


## For agents

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

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- [Inkling 2 Small vs Nanbeige4.2-3B](https://www.anchorterminal.com/compare/inkling-2-small-vs-nanbeige-4-2-3b.md)
- [Inkling 2 Small vs Nanbeige4.3-33B](https://www.anchorterminal.com/compare/inkling-2-small-vs-nanbeige-4-3-33b.md)
- [Inkling 2 Small vs NVIDIA Nemotron 3.5 Bolt E4B 4GB](https://www.anchorterminal.com/compare/inkling-2-small-vs-nemotron-3-5-bolt-e4b-4gb.md)
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- [Inkling 2 Small vs Nemotron 3 Nano Omni 30B A3B Reasoning](https://www.anchorterminal.com/compare/inkling-2-small-vs-nemotron-3-nano-omni-30b-a3b-reasoning.md)
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- [Inkling 2 Small vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/inkling-2-small-vs-ornith-1-5-122b.md)
- [Inkling 2 Small vs Ornith-1.5-35B-A3B](https://www.anchorterminal.com/compare/inkling-2-small-vs-ornith-1-5-35b-a3b.md)
- [Inkling 2 Small vs Ornith-1.5-397B](https://www.anchorterminal.com/compare/inkling-2-small-vs-ornith-1-5-397b.md)
- [Inkling 2 Small vs Ornith-1.5-9B](https://www.anchorterminal.com/compare/inkling-2-small-vs-ornith-1-5-9b.md)
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- [Inkling 2 Small vs Qwen3-4B-Instruct-2507](https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-4b-instruct-2507.md)
- [Inkling 2 Small vs Qwen3.5-0.8B](https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-5-0-8b.md)
- [Inkling 2 Small vs Qwen3.5-122B-A10B](https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-5-122b-a10b.md)
- [Inkling 2 Small vs Qwen3.5-2B](https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-5-2b.md)
- [Inkling 2 Small vs Qwen3.5-397B-A17B](https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-5-397b-a17b.md)
- [Inkling 2 Small vs Qwen3.5-4B](https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-5-4b.md)
- [Inkling 2 Small vs Qwen3.5-9B](https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-5-9b.md)
- [Inkling 2 Small vs Qwen3.6-27B](https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-6-27b.md)
- [Inkling 2 Small vs Qwen3.6-35B-A3B](https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-6-35b-a3b.md)
- [Inkling 2 Small vs Qwen3.8-27B](https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-8-27b.md)
- [Inkling 2 Small vs Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-8-flash-next.md)
- [Inkling 2 Small vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-coder-30b-a3b-instruct.md)
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- [Inkling 2 Small vs Qwen3-VL-2B-Instruct](https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-vl-2b-instruct.md)
- [Inkling 2 Small vs Qwen3-VL-30B-A3B-Instruct](https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-vl-30b-a3b-instruct.md)
- [Inkling 2 Small vs Qwen3-VL-32B-Instruct](https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-vl-32b-instruct.md)
- [Inkling 2 Small vs Qwen3-VL-4B-Instruct](https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-vl-4b-instruct.md)
- [Inkling 2 Small vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-vl-8b-instruct.md)
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- [Inkling 2 Small vs Spark-X2.6-4B](https://www.anchorterminal.com/compare/inkling-2-small-vs-spark-x2-6-4b.md)
- [Inkling 2 Small vs Step 3.7 Flash](https://www.anchorterminal.com/compare/inkling-2-small-vs-step-3-7-flash.md)
- [Inkling 2 Small vs Swift 1.5 Qwen3.8-27B](https://www.anchorterminal.com/compare/inkling-2-small-vs-swift-1-5-qwen3-8-27b.md)
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- [Inkling 2 Small vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/inkling-2-small-vs-thinkingcap-qwen3-8-27b.md)
- [Inkling 2 Small vs Baidu Unlimited-OCR-2](https://www.anchorterminal.com/compare/inkling-2-small-vs-unlimited-ocr-2.md)
- [Inkling 2 Small vs WeVisOne-VL-2B](https://www.anchorterminal.com/compare/inkling-2-small-vs-wevisone-vl-2b.md)
- [Inkling 2 Small vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/inkling-2-small-vs-wevisone-vl-4b.md)
- [Inkling 2 Small vs ZAYA1-8B](https://www.anchorterminal.com/compare/inkling-2-small-vs-zaya1-8b.md)
- [Inkling-Small vs SmolLM3-3B](https://www.anchorterminal.com/compare/inkling-small-vs-smollm3-3b.md)
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- [LFM3-Omni-2B vs SmolLM3-3B](https://www.anchorterminal.com/compare/lfm3-omni-2b-vs-smollm3-3b.md)
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- [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)
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- [Muse Glimmer 30B vs SmolLM3-3B](https://www.anchorterminal.com/compare/muse-glimmer-30b-vs-smollm3-3b.md)
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- [Nemotron 3 Nano 4B vs SmolLM3-3B](https://www.anchorterminal.com/compare/nemotron-3-nano-4b-vs-smollm3-3b.md)
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- [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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