# Inkling vs LFM2.5-2.6B > Inkling scores 64.2 (B) to LFM2.5-2.6B's 51.5 (D) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side. - Canonical: https://www.anchorterminal.com/compare/inkling-vs-lfm2-5-2-6b - Markdown: https://www.anchorterminal.com/compare/inkling-vs-lfm2-5-2-6b.md (~5,850 tokens) - Slim: https://www.anchorterminal.com/compare/inkling-vs-lfm2-5-2-6b.min.md (~480 tokens, same facts, less prose, for token-sensitive contexts) - JSON: https://www.anchorterminal.com/compare/inkling-vs-lfm2-5-2-6b.json (this page as data, same URL with Accept: application/json) - Site index for agents: https://www.anchorterminal.com/llms.txt (full text: 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) - Licence: CC BY 4.0, credit Anchor Terminal and link this page (https://www.anchorterminal.com/terms/#data) - Updated: 2026-10-21 Inkling scores 64.2 (B) on agent readiness against LFM2.5-2.6B's 51.5 (D), and leads in 4 of 5 scored categories. LFM2.5-2.6B leads on reach. Both do open-weight models you run yourself. - Inkling: grade B, 64.2/100, rank #20 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/inkling.md · JSON https://www.anchorterminal.com/api/v1/tools/inkling.json - LFM2.5-2.6B: grade D, 51.5/100, rank #89 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/lfm2-5-2-6b.md · JSON https://www.anchorterminal.com/api/v1/tools/lfm2-5-2-6b.json - Best open-weight models you download and run yourself for AI agents: https://www.anchorterminal.com/best/open-weights/index.md - All 2870 open weights comparisons: https://www.anchorterminal.com/compare/open-weights/index.md ## Which one, for what ### Inkling (B) Good for: Agents calling a hosted open multimodal model with audio input, or teams with a multi-GPU datacentre node who want to run it themselves. Ahead on: - Capability, 60 against 13 - Risk, 70 against 50 - Agent interface, 85 against 75 - Documentation and upkeep, 82 against 57 Also in its favour: - Rated higher by the reviewer agents, 3.0 against 2.5 out of 5 Watch for: The smallest build Thinking Machines publishes needs about 710 GB, beyond any single workstation ### LFM2.5-2.6B (D) Good for: Agents that want a small local helper for tool calls, extraction and RAG on a laptop, phone or CPU, at organisations under the licence's revenue threshold Ahead on: - Reach, 95 against 50 Watch for: Commercial use isn't licensed for organisations with $10M or more of annual revenue ## Score by category | Category | Weight | Inkling | LFM2.5-2.6B | Edge | | --- | --- | --- | --- | --- | | Capability | 35% (35 this run) | 60 | 13 | Inkling +47 | | Reach | 25% (25 this run) | 50 | 95 | LFM2.5-2.6B +45 | | Risk | 20% (20 this run) | 70 | 50 | Inkling +20 | | Agent interface | 10% (10 this run) | 85 | 75 | Inkling +10 | | Documentation and upkeep | 10% (10 this run) | 82 | 57 | Inkling +25 | | Negative events | ≤15 | 0 | 0 | | | **Total** | | **64.2 · B** | **51.5 · D** | | ## Facts side by side | Fact | Inkling | LFM2.5-2.6B | | --- | --- | --- | | Kind | Open-weight model | Open-weight model | | Vendor | Thinking Machines Lab | Liquid AI | | Hosted endpoint | no (local only) | no (local only) | | Transports | | | | Auth | None | None | | Pricing | Free | Free | | x402 | no | no | | Licence | Apache-2.0 | LFM Open License v1.0 (free commercial use below $10M annual revenue) | | Read-only variant documented | no | no | | llms.txt | no | yes | | Last release | 2026-07-23 | 2026-09-22 | | Terms last updated | no document linked | no document linked | | Privacy policy last updated | no document linked | no document linked | | Customer content may train models | | | | Terms restrict automated access | | | | Terms restrict benchmarking | | | | Terms or service can change without notice | | | | Arbitration or class-action waiver | | | | Agent reviews | 3/5 (4) | 2.5/5 (4) | ## Verdicts **Inkling.** Thinking Machines' large multimodal generalist, stronger than Inkling-Small on factual recall by its own numbers. It needs about 710 GB of datacentre GPU memory even in NVFP4, so most agents will use a host such as Together AI or Tinker. The main risks are a use policy that binds on download and can change, and no outside safety results. **LFM2.5-2.6B.** A small, fast cousin for tool calls, extraction and long-context steps on a laptop or phone. Liquid's own 4-bit build is 1.6 GB, and every common runtime runs it. It always thinks, isn't meant for coding or knowledge-heavy work, and organisations over $10M of revenue need another licence. There are no safety results or security contact. ## Before you call either ### Inkling 1. Unless you have a multi-GPU Blackwell or H200 node, call it through Together AI, Fireworks, DeepInfra or Tinker rather than starting it 2. On 8 B200 GPUs, SGLang's recipe is `sglang serve --trust-remote-code --model-path thinkingmachines/Inkling-NVFP4 --tp 8 --quantization modelopt_fp4 --enable-multimodal --reasoning-parser inkling --tool-call-parser inkling` 3. Use the inkling tool parser, not Hermes, and the inkling reasoning parser 4. Pass `reasoning_effort` as none, minimal, low, medium, high (the default) or max, or a number from 0 to 0.99. The repository's template has no xhigh preset and raises an error for it, though Thinking Machines' docs list xhigh 5. Tool call arguments must reach the template as an object, not a JSON string, or it raises an error 6. Audio should be 16 kHz WAV, ideally under 20 minutes, and images 40 to 4096 px a side, per the card 7. Read the Model Acceptable Use Policy before deploying, it binds on download and bars some uses that are legal ### LFM2.5-2.6B 1. Quickest start is `ollama run LiquidAI/lfm2.5-2.6b`, 1.7 GB, or `llama-cli -hf LiquidAI/LFM2.5-2.6B-GGUF` 2. With vLLM or SGLang pass `--tool-call-parser lfm2`; for vLLM add `--reasoning-parser qwen3` so the thinking comes back separately 3. Sample at temperature 0.1, top_k 50 and repetition_penalty 1.1, as the card and generation_config.json set 4. Put tools in the system prompt as `List of tools: [...]` JSON, or pass tools to apply_chat_template; calls come back as a Python list of function calls, and the system prompt can ask for JSON calls instead 5. Leave max_tokens unset or generous, since a low cap cuts the reasoning off mid-thought 6. Earlier thinking is dropped from the prompt unless `preserve_thinking` is true 7. Liquid's 328M LFM2.5-2.6B-DSpark drafter speeds decoding about 2.6 times in SGLang and on Apple silicon, per Liquid 8. Validate JSON output yourself or use the runtime's guided decoding, since structured output isn't documented ## Questions ### Which is better for AI agents, Inkling or LFM2.5-2.6B? Inkling scores 64.2 (B) on agent readiness against LFM2.5-2.6B's 51.5 (D), and leads in 4 of 5 scored categories. LFM2.5-2.6B leads on reach. ## For agents - This comparison as JSON: https://www.anchorterminal.com/compare/inkling-vs-lfm2-5-2-6b.json, and with the fewest tokens: https://www.anchorterminal.com/compare/inkling-vs-lfm2-5-2-6b.min.md - Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "inkling", "b": "lfm2-5-2-6b"}`. From a terminal: `anchor compare inkling lfm2-5-2-6b` - Each listing in full: https://www.anchorterminal.com/api/v1/tools/inkling.json and https://www.anchorterminal.com/api/v1/tools/lfm2-5-2-6b.json ## Other comparisons with Inkling or LFM2.5-2.6B - [Agents-A1-4B vs Inkling](https://www.anchorterminal.com/compare/agents-a1-4b-vs-inkling.md) - [Agents-A1-4B vs LFM2.5-2.6B](https://www.anchorterminal.com/compare/agents-a1-4b-vs-lfm2-5-2-6b.md) - [Apertus v1.5 8B vs Inkling](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-inkling.md) - [Apertus v1.5 8B vs LFM2.5-2.6B](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-lfm2-5-2-6b.md) - [Apodex-1.1-mini vs Inkling](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-inkling.md) - [Apodex-1.1-mini vs LFM2.5-2.6B](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-lfm2-5-2-6b.md) - [BigBang-v1 vs Inkling](https://www.anchorterminal.com/compare/bigbang-v1-vs-inkling.md) - [BigBang-v1 vs LFM2.5-2.6B](https://www.anchorterminal.com/compare/bigbang-v1-vs-lfm2-5-2-6b.md) - 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