# Apertus v1.5 8B vs Olmo 3 7B Think

> Apertus v1.5 8B scores 61 (C) to Olmo 3 7B Think's 52.3 (D) 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-olmo-3-7b-think
- Markdown: https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-olmo-3-7b-think.md (~6,200 tokens)
- Slim: https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-olmo-3-7b-think.min.md (~480 tokens, same facts, less prose, for token-sensitive contexts)
- JSON: https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-olmo-3-7b-think.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

Apertus v1.5 8B scores 61 (C) on agent readiness against Olmo 3 7B Think's 52.3 (D), and leads in 2 of 4 scored categories. Olmo 3 7B Think leads on reach. Both do open-weight models you run yourself.

- Apertus v1.5 8B: grade C, 61/100, rank #35 of 100 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
- Olmo 3 7B Think: grade D, 52.3/100, rank #86 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/olmo-3-7b-think.md · JSON https://www.anchorterminal.com/api/v1/tools/olmo-3-7b-think.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

### 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:
- Agent interface, 85 against 35
- Documentation and upkeep, 84 against 52

Watch for: No released runtime supports it, only Swiss AI's forks of vLLM and Transformers

### Olmo 3 7B Think (D)

Good for: Researchers and agents that want a small fully open reasoning model for maths and code, with its training data on hand

Ahead on:
- Reach, 75 against 40

Watch for: Not trained for tool calling, and the tool format lives only in the template


## Score by category

| Category | Weight | Apertus v1.5 8B | Olmo 3 7B Think | Edge |
| --- | --- | --- | --- | --- |
| Capability | 35%, pending | pending | pending | not scored in this run |
| Reach | 25% (25 this run) | 40 | 75 | Olmo 3 7B Think +35 |
| Risk | 20% (20 this run) | 75 | 75 | even |
| Agent interface | 10% (10 this run) | 85 | 35 | Apertus v1.5 8B +50 |
| Documentation and upkeep | 10% (10 this run) | 84 | 52 | Apertus v1.5 8B +32 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **61 · C** | **52.3 · D** | |

## Facts side by side

| Fact | Apertus v1.5 8B | Olmo 3 7B Think |
| --- | --- | --- |
| Kind | Open-weight model | Open-weight model |
| Vendor | Swiss AI Initiative (EPFL and ETH Zurich) | Ai2 (Allen Institute for AI) |
| 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, with Ai2's Responsible Use Guidelines named on the card |
| Read-only variant documented | no | no |
| llms.txt | no | no |
| Last release | 2026-10-14 | 2026-06-25 |
| Terms last updated |  |  |
| Privacy policy last updated | 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 | 2.8/5 (4) | 2.8/5 (4) |

## 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.

**Olmo 3 7B Think.** A fully open 7B reasoning cousin for maths, code and step-by-step answers, with every dataset and checkpoint published and its safety results rerunnable. Ollama's 4-bit build needs about 5.4 GB. It always thinks, wasn't trained for tool calls, has 65K of context, and Ai2 hasn't answered its discussions.

## 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

### Olmo 3 7B Think

1. Quickest start is `ollama run olmo-3:7b-think`, about 4.5 GB
2. With vLLM, `vllm serve allenai/Olmo-3-7B-Think --max-model-len 65536`; vLLM runs it through its Transformers backend
3. Sample at temperature 0.6 and top_p 0.95 with up to 32,768 output tokens, as the card recommends, since thinking traces are long
4. Every reply starts with a think block; strip it yourself or use a reasoning parser that reads think tags
5. Pass your own system prompt; the template's default says the cut-off is November 2024 and that no functions are available
6. For tool calls use Olmo 3 7B Instruct instead, which Ai2 trained for function calling
7. A discussion reports endless reasoning loops when served with vLLM, unanswered, so cap max_tokens
8. Check the use against Ai2's Responsible Use Guidelines, which bar automated social-media posting and undisclosed automated content outside research

## Questions

### Which is better for AI agents, Apertus v1.5 8B or Olmo 3 7B Think?

Apertus v1.5 8B scores 61 (C) on agent readiness against Olmo 3 7B Think's 52.3 (D), and leads in 2 of 4 scored categories. Olmo 3 7B Think leads on reach.


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-olmo-3-7b-think.json, and with the fewest tokens: https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-olmo-3-7b-think.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "apertus-v1-5-8b", "b": "olmo-3-7b-think"}`. From a terminal: `anchor compare apertus-v1-5-8b olmo-3-7b-think`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/apertus-v1-5-8b.json and https://www.anchorterminal.com/api/v1/tools/olmo-3-7b-think.json

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- [Granite 4.2 3B vs Olmo 3 7B Think](https://www.anchorterminal.com/compare/granite-4-2-3b-vs-olmo-3-7b-think.md)
- [Hy3 vs Olmo 3 7B Think](https://www.anchorterminal.com/compare/hy3-vs-olmo-3-7b-think.md)
- [Inkling-Small vs Olmo 3 7B Think](https://www.anchorterminal.com/compare/inkling-small-vs-olmo-3-7b-think.md)
- [Inkling vs Olmo 3 7B Think](https://www.anchorterminal.com/compare/inkling-vs-olmo-3-7b-think.md)
- [InternVL3.5-GPT-OSS-20B-A4B-Preview vs Olmo 3 7B Think](https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-olmo-3-7b-think.md)
- [Kimi K3 vs Olmo 3 7B Think](https://www.anchorterminal.com/compare/kimi-k3-vs-olmo-3-7b-think.md)
- [Kolibri-1 vs Olmo 3 7B Think](https://www.anchorterminal.com/compare/kolibri-1-vs-olmo-3-7b-think.md)
- [Laguna M.1 vs Olmo 3 7B Think](https://www.anchorterminal.com/compare/laguna-m-1-vs-olmo-3-7b-think.md)
- [Laguna S 2.1 vs Olmo 3 7B Think](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-olmo-3-7b-think.md)
- [Laguna XS 2.1 vs Olmo 3 7B Think](https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-olmo-3-7b-think.md)
- [LFM2.5-2.6B vs Olmo 3 7B Think](https://www.anchorterminal.com/compare/lfm2-5-2-6b-vs-olmo-3-7b-think.md)
- [Ling-3.0-tiny vs Olmo 3 7B Think](https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-olmo-3-7b-think.md)
- [MiMo-V2.6 Distill Qwen 9B vs Olmo 3 7B Think](https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-olmo-3-7b-think.md)
- [MiniCPM-o 4.5 vs Olmo 3 7B Think](https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-olmo-3-7b-think.md)
- [MiniCPM5-2B vs Olmo 3 7B Think](https://www.anchorterminal.com/compare/minicpm5-2b-vs-olmo-3-7b-think.md)
- [MiniMax-M2.5 vs Olmo 3 7B Think](https://www.anchorterminal.com/compare/minimax-m2-5-vs-olmo-3-7b-think.md)
- [MiniMax-M2.7 vs Olmo 3 7B Think](https://www.anchorterminal.com/compare/minimax-m2-7-vs-olmo-3-7b-think.md)
- [Muse Glimmer 30B vs Olmo 3 7B Think](https://www.anchorterminal.com/compare/muse-glimmer-30b-vs-olmo-3-7b-think.md)
- [Nemotron 3.5 Lightning 30B A3B vs Olmo 3 7B Think](https://www.anchorterminal.com/compare/nemotron-3-5-lightning-30b-a3b-vs-olmo-3-7b-think.md)
- [Nemotron 3 Nano 30B A3B vs Olmo 3 7B Think](https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-olmo-3-7b-think.md)
- [Nemotron 3 Nano 4B vs Olmo 3 7B Think](https://www.anchorterminal.com/compare/nemotron-3-nano-4b-vs-olmo-3-7b-think.md)
- [Nemotron 3 Nano Omni 30B A3B Reasoning vs Olmo 3 7B Think](https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-olmo-3-7b-think.md)
- [Nemotron 3 Super 120B A12B vs Olmo 3 7B Think](https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-olmo-3-7b-think.md)
- [Nemotron 3 Ultra 550B A55B vs Olmo 3 7B Think](https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-olmo-3-7b-think.md)
- [occamy-1.0 vs Olmo 3 7B Think](https://www.anchorterminal.com/compare/occamy-1-0-vs-olmo-3-7b-think.md)
- [Olmo 3 7B Think vs Ornith-1.5-35B-A3B](https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-ornith-1-5-35b-a3b.md)
- [Olmo 3 7B Think vs Ornith-1.5-397B](https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-ornith-1-5-397b.md)
- [Olmo 3 7B Think vs Ornith-1.5-9B](https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-ornith-1-5-9b.md)
- [Olmo 3 7B Think vs Qwen3-30B-A3B-Instruct-2507](https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-30b-a3b-instruct-2507.md)
- [Olmo 3 7B Think vs Qwen3-4B-Instruct-2507](https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-4b-instruct-2507.md)
- [Olmo 3 7B Think vs Qwen3.5-0.8B](https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-5-0-8b.md)
- [Olmo 3 7B Think vs Qwen3.5-122B-A10B](https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-5-122b-a10b.md)
- [Olmo 3 7B Think vs Qwen3.5-2B](https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-5-2b.md)
- [Olmo 3 7B Think vs Qwen3.5-397B-A17B](https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-5-397b-a17b.md)
- [Olmo 3 7B Think vs Qwen3.5-4B](https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-5-4b.md)
- [Olmo 3 7B Think vs Qwen3.5-9B](https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-5-9b.md)
- [Olmo 3 7B Think vs Qwen3.6-27B](https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-6-27b.md)
- [Olmo 3 7B Think vs Qwen3.6-35B-A3B](https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-6-35b-a3b.md)
- [Olmo 3 7B Think vs Qwen3.8-27B](https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-8-27b.md)
- [Olmo 3 7B Think vs Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-8-flash-next.md)
- [Olmo 3 7B Think vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-coder-30b-a3b-instruct.md)
- [Olmo 3 7B Think vs Qwen3-Coder-Next](https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-coder-next.md)
- [Olmo 3 7B Think vs Qwen3-Omni-30B-A3B-Instruct](https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-omni-30b-a3b-instruct.md)
- [Olmo 3 7B Think vs Qwen3-VL-2B-Instruct](https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-vl-2b-instruct.md)
- [Olmo 3 7B Think vs Qwen3-VL-30B-A3B-Instruct](https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-vl-30b-a3b-instruct.md)
- [Olmo 3 7B Think vs Qwen3-VL-32B-Instruct](https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-vl-32b-instruct.md)
- [Olmo 3 7B Think vs Qwen3-VL-4B-Instruct](https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-vl-4b-instruct.md)
- [Olmo 3 7B Think vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-vl-8b-instruct.md)
- [Olmo 3 7B Think vs Qwopus3.8-27B-Flash-V2](https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwopus3-8-27b-flash-v2.md)
- [Olmo 3 7B Think vs SmolLM3-3B](https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-smollm3-3b.md)
- [Olmo 3 7B Think vs Spark-X2.6-4B](https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-spark-x2-6-4b.md)
- [Olmo 3 7B Think vs Swift 1.5 Qwen3.8-27B](https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-swift-1-5-qwen3-8-27b.md)
- [Olmo 3 7B Think vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-swift-1-5-qwen3-8-flash-next.md)
- [Olmo 3 7B Think vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-thinkingcap-qwen3-8-27b.md)

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