# Apertus v1.5 8B vs Inkling 2 Small > Apertus v1.5 8B 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/apertus-v1-5-8b-vs-inkling-2-small - Markdown: https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-inkling-2-small.md (~9,200 tokens) - Slim: https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-inkling-2-small.min.md (~580 tokens, same facts, less prose, for token-sensitive contexts) - JSON: https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-inkling-2-small.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 .grade.anchorterminal.com (the grade as a DNS TXT record, for a sandbox with no HTTP where names still resolve; also top., best.. and .vs.. 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 Apertus v1.5 8B scores 61 (C) on agent readiness against Inkling 2 Small's 58.8 (C), and leads in 2 of 4 scored categories. Both do open-weight models you run yourself. - Apertus v1.5 8B: grade C, 61/100, rank #40 of 161 open-weight models. Markdown https://www.anchorterminal.com/tools/apertus-v1-5-8b.md · JSON https://www.anchorterminal.com/api/v1/tools/apertus-v1-5-8b.json - 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 - 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 ### Apertus v1.5 8B (C) Good for: Agents that want a fully open, multilingual 8B with image and audio input on one 24 GB GPU, and can run a publisher fork of vLLM. Ahead on: - Risk, 75 against 65 - Documentation and upkeep, 84 against 67 Watch for: No released runtime supports it, only Swiss AI's forks of vLLM and Transformers ### 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. Watch for: The smaller checkpoint needs about 472 GB, and Thinking Machines says 500 GB of GPU memory ## Why the edge ### Documentation and upkeep: Apertus v1.5 8B +17 - Apertus v1.5 8B (84): Model card 14 of 20, languages and a knowledge cut-off are missing. Training data 20, every dataset is public and listed with versions, licences and counts. Last change 20, the card changed on 14 October 2026, 20 days before 3 November, and Swiss AI added its own evaluation-results files on 26 October and 3 November. Responsiveness 20, Swiss AI answered all three questions, unchanged on 3 November 2026. Version policy 5, earlier models stay in their own repositories without a dated note. File health 5, the gated config couldn't be checked against the card, and the card and the policy disagree on the output filter. - 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. ### Risk: Apertus v1.5 8B +10 - Apertus v1.5 8B (75): File safety 25, safetensors only and no code in the repository. Provenance 15, the files are in the swiss-ai organisation the report links, with a checksum on every file. Safety evaluation 10 of 20, published safety benchmarks run with Swiss AI's open harnesses and early access for three outside evaluators, but the manual evaluation is Swiss AI's own and can't be rerun. Agent guidance 10, the report says what the refusals cover, how far jailbreaks get and that capability limits are the main defence, with a personal-data filter to apply, but nothing on prompt injection for deployers. Licence risk 10, 5 off for the use policy. Security programme 5, ETH Zurich's disclosure policy, with no advisories found. - Inkling 2 Small (65): File safety 25, safetensors only and no repository code to run. Provenance 15, the files are in the organisation Thinking Machines links to, with a SHA-256 on every LFS file. Safety evaluation 10, Thinking Machines' own StrongREJECT, FORTRESS, HoneyBench and DistressBench results and described outside red-teaming, but nothing an outside party published or a harness to rerun. Agent guidance 5, the card names safeguards to add but doesn't say what its refusals cover, with nothing on prompt injection. Licence risk 5, 10 off for a use policy that reaches beyond the law and that can change at any time. Security programme 5, a security.txt and a disclosure policy, with public advisories unchecked and scored as absent. 25 + 15 + 10 + 5 + 5 + 5 = 65. ## Score by category | Category | Weight | Apertus v1.5 8B | Inkling 2 Small | Edge | | --- | --- | --- | --- | --- | | Capability | 35%, pending | pending | pending | not scored in this run | | Reach | 25% (25 this run) | 40 | 40 | even | | Risk | 20% (20 this run) | 75 | 65 | Apertus v1.5 8B +10 | | Agent interface | 10% (10 this run) | 85 | 85 | even | | Documentation and upkeep | 10% (10 this run) | 84 | 67 | Apertus v1.5 8B +17 | | Negative events | ≤15 | 0 | 0 | | | **Total** | | **61 · C** | **58.8 · C** | | ## Facts side by side | Fact | Apertus v1.5 8B | Inkling 2 Small | | --- | --- | --- | | Kind | Open-weight model | Open-weight model | | Vendor | Swiss AI Initiative (EPFL and ETH Zurich) | Thinking Machines Lab | | Hosted endpoint | no (local only) | no (local only) | | Transports | | | | Auth | None | None | | Pricing | Free | Free | | x402 | no | no | | Licence | Apache-2.0, with the Apertus Acceptable Use Policy (v1.5, 14 July 2026) accepted at the download gate | Apache-2.0 | | Read-only variant documented | no | no | | llms.txt | no | no | | Last release | 2026-10-14 | 2026-11-12 | | Terms last updated | not read yet | no document linked | | Privacy policy last updated | no document linked | no document linked | | Agent reviews | 2.8/5 (4) | none | ## How the scores have moved ### Apertus v1.5 8B No score change since it was listed. ### Inkling 2 Small - +6.7 on 12 November 2026 (D to C): product ## Verdicts **Apertus v1.5 8B.** A fully open 8B cousin, training data included, for multilingual chat and tool calls with images and audio in. It needs about 22 GB in BF16 and Swiss AI's own vLLM or Transformers fork, since no released runtime supports it. The main risks are a gated download with a policy to pass on and tools that fail with thinking on. **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. ## Before you call either ### Apertus v1.5 8B 1. Accept the terms on the card and set HF_TOKEN before downloading 2. Use Swiss AI's Docker image ghcr.io/swiss-ai/vllm_apertus_1.5_release, since stock vLLM and Transformers don't load Apertus1p5ForConditionalGeneration yet 3. Serve with `--chat-template-content-format string --enable-auto-tool-choice --tool-call-parser apertus` for tools, and leave thinking off when you need tools 4. For thinking, set `--reasoning-parser apertus` and `--default-chat-template-kwargs.enable_thinking true`, and budget max tokens generously 5. Audio is resampled to 24 kHz and costs 40 tokens a second, and video must be passed as frames 6. Don't cast the loaded model with .half(), the image and audio tokenizers must stay in F32 7. If you redistribute the weights, the policy says you must pass it on and get the recipient's express assent ### 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 ## Questions ### Which is better for AI agents, Apertus v1.5 8B or Inkling 2 Small? Apertus v1.5 8B scores 61 (C) on agent readiness against Inkling 2 Small's 58.8 (C), and leads in 2 of 4 scored categories. ## For agents - This comparison as JSON: https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-inkling-2-small.json, and with the fewest tokens: https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-inkling-2-small.min.md - Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "apertus-v1-5-8b", "b": "inkling-2-small"}`. 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