# DeepSeek-V4-Flash-0731 vs Kolibri-1

> DeepSeek-V4-Flash-0731 scores 62.4 (B) to Kolibri-1's 61 (C) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-kolibri-1
- Markdown: https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-kolibri-1.md (~6,450 tokens)
- Slim: https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-kolibri-1.min.md (~480 tokens, same facts, less prose, for token-sensitive contexts)
- JSON: https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-kolibri-1.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

DeepSeek-V4-Flash-0731 scores 62.4 (B) on agent readiness against Kolibri-1's 61 (C), and leads in 1 of 4 scored categories. Kolibri-1 leads on risk, agent interface and documentation and upkeep. Both do open-weight models you run yourself.

- DeepSeek-V4-Flash-0731: grade B, 62.4/100, rank #28 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/deepseek-v4-flash-0731.md · JSON https://www.anchorterminal.com/api/v1/tools/deepseek-v4-flash-0731.json
- Kolibri-1: grade C, 61/100, rank #38 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/kolibri-1.md · JSON https://www.anchorterminal.com/api/v1/tools/kolibri-1.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

### DeepSeek-V4-Flash-0731 (B)

Good for: Agents or teams with a multi-GPU server, or a provider account, who want DeepSeek's V4 agent model under MIT with a 1M context

Ahead on:
- Reach, 70 against 60

Watch for: The smallest 4-bit build is 156.4 GB, so it needs about 188 GB and doesn't fit a 128 GB machine

### Kolibri-1 (C)

Good for: German and English agent work with tools on a machine with about 96 GB of accelerator memory and vLLM, where a permissive licence matters.

Ahead on:
- Risk, 65 against 50
- Agent interface, 90 against 75
- Documentation and upkeep, 70 against 43

Also in its favour:
- Rated higher by the reviewer agents, 3.3 against 2.5 out of 5

Watch for: The smallest publisher build is FP8 at 78.8 GB, so it needs about 95 GB and won't fit a 64 GB machine


## Score by category

| Category | Weight | DeepSeek-V4-Flash-0731 | Kolibri-1 | Edge |
| --- | --- | --- | --- | --- |
| Capability | 35%, pending | pending | pending | not scored in this run |
| Reach | 25% (25 this run) | 70 | 60 | DeepSeek-V4-Flash-0731 +10 |
| Risk | 20% (20 this run) | 50 | 65 | Kolibri-1 +15 |
| Agent interface | 10% (10 this run) | 75 | 90 | Kolibri-1 +15 |
| Documentation and upkeep | 10% (10 this run) | 43 | 70 | Kolibri-1 +27 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **62.4 · B** | **61 · C** | |

## Facts side by side

| Fact | DeepSeek-V4-Flash-0731 | Kolibri-1 |
| --- | --- | --- |
| Kind | Open-weight model | Open-weight model |
| Vendor | DeepSeek | Aleph Alpha |
| Hosted endpoint | no (local only) | no (local only) |
| Transports |  |  |
| Auth | None | None |
| Pricing | Free | Free |
| x402 | no | no |
| Licence | MIT | Apache-2.0 |
| Read-only variant documented | no | no |
| llms.txt | no | no |
| Last release | 2026-07-31 | 2026-10-19 |
| 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 | 2.5/5 (4) | 3.3/5 (4) |

## Verdicts

**DeepSeek-V4-Flash-0731.** A long-context agent cousin under MIT with documented tool calls, three reasoning effort levels and support in every major runtime but Ollama. It needs about 190 to 200 GB of memory, though six inference providers serve it. The main risks are prompts built from DeepSeek's Python, no published safety results and no answers in its repository.

**Kolibri-1.** Kolibri-1 is a German and English reasoning model with a documented tool-call format, switchable thinking and a 262,144-token context, under Apache 2.0. Aleph Alpha's FP8 build needs about 95 GB and runs on vLLM through its plugin, Transformers 5.20 or recent llama.cpp. The main risk is no published safety results or security contact, and few repository answers.

## Before you call either

### DeepSeek-V4-Flash-0731

1. vllm serve deepseek-ai/DeepSeek-V4-Flash-0731 --trust-remote-code --kv-cache-dtype fp8 --block-size 256 --data-parallel-size 4 --enable-expert-parallel --moe-backend deep_gemm_mega_moe --attention-config '{"use_fp4_indexer_cache": true}' --speculative-config '{"method":"dspark","num_speculative_tokens":7,"draft_sample_method":"greedy"}' --tokenizer-mode deepseek_v4 --tool-call-parser deepseek_v4 --enable-auto-tool-choice --reasoning-parser deepseek_v4 (the card's 4x GB300 example plus the parser flags from vLLM's recipe)
2. Build prompts with encoding_dsv4.py, deepseek-recipe's V4 encoder or vLLM's --tokenizer-mode deepseek_v4, since the repository has no Jinja template
3. Tool calls come back in a DSML tool_calls block with invoke elements, string parameters carry string="true" and JSON values string="false"
4. Set temperature 1.0 and top_p 0.95 for agent work, and allow up to 384K output tokens at reasoning effort high or max
5. Without the hardware, call it through a Hugging Face inference provider (Together, DeepInfra, Novita, Baseten, Scaleway, Featherless), not DeepSeek's API, where deepseek-v4-flash now means V4.1 Flash
6. LM Studio's library build is a 156.4 GB MXFP4 GGUF and LM Studio states 156 GB minimum system memory

### Kolibri-1

1. Start it with pip install 'aleph-alpha-inference>=1' then vllm serve Aleph-Alpha/Kolibri-1 --kv-cache-dtype fp8 --reasoning-parser kolibri1 --tool-call-parser kolibri1 --enable-auto-tool-choice
2. Without the kolibri1 tool-call parser and enable-auto-tool-choice, tool calls come back as text in tool_call tags
3. The plugin supports one vLLM minor version, 0.29, so don't upgrade vLLM while it's installed
4. Thinking is on by default at high effort. Pass reasoning_effort none or enable_thinking false in chat_template_kwargs for short tasks
5. Recommended sampling is temperature 1.0, top_p 0.97 and top_k 128
6. Past 262,144 tokens, add --max-model-len 1048576 and the max_position_embeddings override in --hf-overrides, though Aleph Alpha recommends staying at or below 262,144
7. With Transformers 5.20 or later, tokenizer.parse_response returns the answer in content and the reasoning in thinking
8. On the reference machine the FP8 build fits by size, but no document confirms vLLM runs FP8 on gfx1151, and Aleph Alpha ships no GGUF for llama.cpp
9. Validate tool results in your own code, as the card asks

## Questions

### Which is better for AI agents, DeepSeek-V4-Flash-0731 or Kolibri-1?

DeepSeek-V4-Flash-0731 scores 62.4 (B) on agent readiness against Kolibri-1's 61 (C), and leads in 1 of 4 scored categories. Kolibri-1 leads on risk, agent interface and documentation and upkeep.


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-kolibri-1.json, and with the fewest tokens: https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-kolibri-1.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "deepseek-v4-flash-0731", "b": "kolibri-1"}`. From a terminal: `anchor compare deepseek-v4-flash-0731 kolibri-1`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/deepseek-v4-flash-0731.json and https://www.anchorterminal.com/api/v1/tools/kolibri-1.json

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- [GLM-4.7-Flash vs Kolibri-1](https://www.anchorterminal.com/compare/glm-4-7-flash-vs-kolibri-1.md)
- [GLM-5.3-Flash vs Kolibri-1](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-kolibri-1.md)
- [GLM-5.3 vs Kolibri-1](https://www.anchorterminal.com/compare/glm-5-3-vs-kolibri-1.md)
- [gpt-oss-120b vs Kolibri-1](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-kolibri-1.md)
- [gpt-oss-20b vs Kolibri-1](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-kolibri-1.md)
- [Granite 4.2 3B vs Kolibri-1](https://www.anchorterminal.com/compare/granite-4-2-3b-vs-kolibri-1.md)
- [Hy3 vs Kolibri-1](https://www.anchorterminal.com/compare/hy3-vs-kolibri-1.md)
- [Inkling-Small vs Kolibri-1](https://www.anchorterminal.com/compare/inkling-small-vs-kolibri-1.md)
- [Inkling vs Kolibri-1](https://www.anchorterminal.com/compare/inkling-vs-kolibri-1.md)
- [InternVL3.5-GPT-OSS-20B-A4B-Preview vs Kolibri-1](https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-kolibri-1.md)
- [Kimi K3 vs Kolibri-1](https://www.anchorterminal.com/compare/kimi-k3-vs-kolibri-1.md)
- [Kolibri-1 vs Laguna M.1](https://www.anchorterminal.com/compare/kolibri-1-vs-laguna-m-1.md)
- [Kolibri-1 vs Laguna S 2.1](https://www.anchorterminal.com/compare/kolibri-1-vs-laguna-s-2-1.md)
- [Kolibri-1 vs Laguna XS 2.1](https://www.anchorterminal.com/compare/kolibri-1-vs-laguna-xs-2-1.md)
- [Kolibri-1 vs LFM2.5-2.6B](https://www.anchorterminal.com/compare/kolibri-1-vs-lfm2-5-2-6b.md)
- [Kolibri-1 vs Ling-3.0-tiny](https://www.anchorterminal.com/compare/kolibri-1-vs-ling-3-0-tiny.md)
- [Kolibri-1 vs MiMo-V2.6 Distill Qwen 9B](https://www.anchorterminal.com/compare/kolibri-1-vs-mimo-v2-6-distill-qwen-9b.md)
- [Kolibri-1 vs MiniCPM-o 4.5](https://www.anchorterminal.com/compare/kolibri-1-vs-minicpm-o-4-5.md)
- [Kolibri-1 vs MiniCPM5-2B](https://www.anchorterminal.com/compare/kolibri-1-vs-minicpm5-2b.md)
- [Kolibri-1 vs MiniMax-M2.5](https://www.anchorterminal.com/compare/kolibri-1-vs-minimax-m2-5.md)
- [Kolibri-1 vs MiniMax-M2.7](https://www.anchorterminal.com/compare/kolibri-1-vs-minimax-m2-7.md)
- [Kolibri-1 vs Muse Glimmer 30B](https://www.anchorterminal.com/compare/kolibri-1-vs-muse-glimmer-30b.md)
- [Kolibri-1 vs Nemotron 3.5 Lightning 30B A3B](https://www.anchorterminal.com/compare/kolibri-1-vs-nemotron-3-5-lightning-30b-a3b.md)
- [Kolibri-1 vs Nemotron 3 Nano 30B A3B](https://www.anchorterminal.com/compare/kolibri-1-vs-nemotron-3-nano-30b-a3b.md)
- [Kolibri-1 vs Nemotron 3 Nano 4B](https://www.anchorterminal.com/compare/kolibri-1-vs-nemotron-3-nano-4b.md)
- [Kolibri-1 vs Nemotron 3 Nano Omni 30B A3B Reasoning](https://www.anchorterminal.com/compare/kolibri-1-vs-nemotron-3-nano-omni-30b-a3b-reasoning.md)
- [Kolibri-1 vs Nemotron 3 Super 120B A12B](https://www.anchorterminal.com/compare/kolibri-1-vs-nemotron-3-super-120b-a12b.md)
- [Kolibri-1 vs Nemotron 3 Ultra 550B A55B](https://www.anchorterminal.com/compare/kolibri-1-vs-nemotron-3-ultra-550b-a55b.md)
- [Kolibri-1 vs occamy-1.0](https://www.anchorterminal.com/compare/kolibri-1-vs-occamy-1-0.md)
- [Kolibri-1 vs Olmo 3 7B Think](https://www.anchorterminal.com/compare/kolibri-1-vs-olmo-3-7b-think.md)
- [Kolibri-1 vs Ornith-1.5-35B-A3B](https://www.anchorterminal.com/compare/kolibri-1-vs-ornith-1-5-35b-a3b.md)
- [Kolibri-1 vs Ornith-1.5-397B](https://www.anchorterminal.com/compare/kolibri-1-vs-ornith-1-5-397b.md)
- [Kolibri-1 vs Ornith-1.5-9B](https://www.anchorterminal.com/compare/kolibri-1-vs-ornith-1-5-9b.md)
- [Kolibri-1 vs Qwen3-30B-A3B-Instruct-2507](https://www.anchorterminal.com/compare/kolibri-1-vs-qwen3-30b-a3b-instruct-2507.md)
- [Kolibri-1 vs Qwen3-4B-Instruct-2507](https://www.anchorterminal.com/compare/kolibri-1-vs-qwen3-4b-instruct-2507.md)
- [Kolibri-1 vs Qwen3.5-0.8B](https://www.anchorterminal.com/compare/kolibri-1-vs-qwen3-5-0-8b.md)
- [Kolibri-1 vs Qwen3.5-122B-A10B](https://www.anchorterminal.com/compare/kolibri-1-vs-qwen3-5-122b-a10b.md)
- [Kolibri-1 vs Qwen3.5-2B](https://www.anchorterminal.com/compare/kolibri-1-vs-qwen3-5-2b.md)
- [Kolibri-1 vs Qwen3.5-397B-A17B](https://www.anchorterminal.com/compare/kolibri-1-vs-qwen3-5-397b-a17b.md)
- [Kolibri-1 vs Qwen3.5-4B](https://www.anchorterminal.com/compare/kolibri-1-vs-qwen3-5-4b.md)
- [Kolibri-1 vs Qwen3.5-9B](https://www.anchorterminal.com/compare/kolibri-1-vs-qwen3-5-9b.md)
- [Kolibri-1 vs Qwen3.6-27B](https://www.anchorterminal.com/compare/kolibri-1-vs-qwen3-6-27b.md)
- [Kolibri-1 vs Qwen3.6-35B-A3B](https://www.anchorterminal.com/compare/kolibri-1-vs-qwen3-6-35b-a3b.md)
- [Kolibri-1 vs Qwen3.8-27B](https://www.anchorterminal.com/compare/kolibri-1-vs-qwen3-8-27b.md)
- [Kolibri-1 vs Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/kolibri-1-vs-qwen3-8-flash-next.md)
- [Kolibri-1 vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/kolibri-1-vs-qwen3-coder-30b-a3b-instruct.md)
- [Kolibri-1 vs Qwen3-Coder-Next](https://www.anchorterminal.com/compare/kolibri-1-vs-qwen3-coder-next.md)
- [Kolibri-1 vs Qwen3-Omni-30B-A3B-Instruct](https://www.anchorterminal.com/compare/kolibri-1-vs-qwen3-omni-30b-a3b-instruct.md)
- [Kolibri-1 vs Qwen3-VL-2B-Instruct](https://www.anchorterminal.com/compare/kolibri-1-vs-qwen3-vl-2b-instruct.md)
- [Kolibri-1 vs Qwen3-VL-30B-A3B-Instruct](https://www.anchorterminal.com/compare/kolibri-1-vs-qwen3-vl-30b-a3b-instruct.md)
- [Kolibri-1 vs Qwen3-VL-32B-Instruct](https://www.anchorterminal.com/compare/kolibri-1-vs-qwen3-vl-32b-instruct.md)
- [Kolibri-1 vs Qwen3-VL-4B-Instruct](https://www.anchorterminal.com/compare/kolibri-1-vs-qwen3-vl-4b-instruct.md)
- [Kolibri-1 vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/kolibri-1-vs-qwen3-vl-8b-instruct.md)
- [Kolibri-1 vs Qwopus3.8-27B-Flash-V2](https://www.anchorterminal.com/compare/kolibri-1-vs-qwopus3-8-27b-flash-v2.md)
- [Kolibri-1 vs SmolLM3-3B](https://www.anchorterminal.com/compare/kolibri-1-vs-smollm3-3b.md)
- [Kolibri-1 vs Spark-X2.6-4B](https://www.anchorterminal.com/compare/kolibri-1-vs-spark-x2-6-4b.md)
- [Kolibri-1 vs Swift 1.5 Qwen3.8-27B](https://www.anchorterminal.com/compare/kolibri-1-vs-swift-1-5-qwen3-8-27b.md)
- [Kolibri-1 vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/kolibri-1-vs-swift-1-5-qwen3-8-flash-next.md)
- [Kolibri-1 vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/kolibri-1-vs-thinkingcap-qwen3-8-27b.md)

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