# DeepSeek-V4-Flash-0731 vs Inkling-Small

> Inkling-Small scores 66.5 (B) to DeepSeek-V4-Flash-0731's 62.4 (B) 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-inkling-small
- Markdown: https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-inkling-small.md (~6,600 tokens)
- Slim: https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-inkling-small.min.md (~480 tokens, same facts, less prose, for token-sensitive contexts)
- JSON: https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-inkling-small.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-Small scores 66.5 (B) on agent readiness against DeepSeek-V4-Flash-0731's 62.4 (B), and leads in 3 of 5 scored categories. DeepSeek-V4-Flash-0731 leads on reach. 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
- Inkling-Small: grade B, 66.5/100, rank #14 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/inkling-small.md · JSON https://www.anchorterminal.com/api/v1/tools/inkling-small.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 55

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

### Inkling-Small (B)

Good for: Teams with 256 GB or more of datacentre GPU memory who want an open multimodal agent model with audio input and adjustable thinking.

Ahead on:
- Risk, 70 against 50
- Agent interface, 85 against 75
- Documentation and upkeep, 82 against 43

Also in its favour:
- Rated higher by the reviewer agents, 3.5 against 2.5 out of 5

Watch for: The smallest build Thinking Machines publishes needs about 205 GB


## Score by category

| Category | Weight | DeepSeek-V4-Flash-0731 | Inkling-Small | Edge |
| --- | --- | --- | --- | --- |
| Capability | 35% (35 this run) | 66 | 63 | DeepSeek-V4-Flash-0731 +3 |
| Reach | 25% (25 this run) | 70 | 55 | DeepSeek-V4-Flash-0731 +15 |
| Risk | 20% (20 this run) | 50 | 70 | Inkling-Small +20 |
| Agent interface | 10% (10 this run) | 75 | 85 | Inkling-Small +10 |
| Documentation and upkeep | 10% (10 this run) | 43 | 82 | Inkling-Small +39 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **62.4 · B** | **66.5 · B** | |

## Facts side by side

| Fact | DeepSeek-V4-Flash-0731 | Inkling-Small |
| --- | --- | --- |
| Kind | Open-weight model | Open-weight model |
| Vendor | DeepSeek | Thinking Machines Lab |
| 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 | 2026-07-31 |
| 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) | 3.5/5 (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.

**Inkling-Small.** A mixture-of-experts generalist with images and audio in, several tool calls a turn and per-request thinking effort. It needs about 205 GB for Thinking Machines' NVFP4 build on recent NVIDIA or AMD datacentre GPUs, and Tinker or DeepInfra host it. The main risks are a use policy that binds on download and can change, and no outside safety results.

## 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

### Inkling-Small

1. Start the NVFP4 build with SGLang's recipe, `sglang serve --trust-remote-code --model-path thinkingmachines/Inkling-Small-NVFP4 --tp 8 --enable-multimodal --reasoning-parser inkling --tool-call-parser inkling`, on Blackwell for W4A4
2. Use the inkling tool and reasoning parsers in vLLM or SGLang, or Thinking Machines' tml-renderers package to render prompts and parse calls yourself
3. 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 and SGLang's cookbook list xhigh
4. Effort none conditions the model toward no reasoning but doesn't forbid it, and higher effort needs a larger max_tokens
5. Tool call arguments must reach the template as an object, not a JSON string, or it raises an error
6. Images should be 40 to 4096 px a side and audio 16 kHz WAV under two minutes, per the card
7. Use guided decoding or validate JSON yourself, since structured output isn't documented
8. 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, DeepSeek-V4-Flash-0731 or Inkling-Small?

Inkling-Small scores 66.5 (B) on agent readiness against DeepSeek-V4-Flash-0731's 62.4 (B), and leads in 3 of 5 scored categories. DeepSeek-V4-Flash-0731 leads on reach.


## For agents

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

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