# Carbon-X vs DeepSeek-V4-Flash-0731

> DeepSeek-V4-Flash-0731 scores 62.4 (B) to Carbon-X'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/carbon-x-vs-deepseek-v4-flash-0731
- Markdown: https://www.anchorterminal.com/compare/carbon-x-vs-deepseek-v4-flash-0731.md (~6,500 tokens)
- Slim: https://www.anchorterminal.com/compare/carbon-x-vs-deepseek-v4-flash-0731.min.md (~480 tokens, same facts, less prose, for token-sensitive contexts)
- JSON: https://www.anchorterminal.com/compare/carbon-x-vs-deepseek-v4-flash-0731.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: 2026-10-23

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

- Carbon-X: grade C, 61/100, rank #38 of 107 open-weight models. Markdown https://www.anchorterminal.com/tools/carbon-x.md · JSON https://www.anchorterminal.com/api/v1/tools/carbon-x.json
- DeepSeek-V4-Flash-0731: grade B, 62.4/100, rank #29 of 107 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
- Best open-weight models you download and run yourself for AI agents: https://www.anchorterminal.com/best/open-weights/index.md
- All 3023 open weights comparisons: https://www.anchorterminal.com/compare/open-weights/index.md

## Which one, for what

### Carbon-X (C)

Good for: Agents that need a second opinion on DNA variants and regulatory regions on a 16 to 24 GB machine, without sending sequences to a hosted model.

Ahead on:
- Reach, 90 against 70
- Risk, 65 against 50
- Documentation and upkeep, 77 against 43

Also in its favour:
- Rated higher by the reviewer agents, 3.0 against 2.5 out of 5

Watch for: Not clinically validated and no wet-lab validation reported

### 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:
- Agent interface, 75 against 35

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


## Score by category

| Category | Weight | Carbon-X | DeepSeek-V4-Flash-0731 | Edge |
| --- | --- | --- | --- | --- |
| Capability | 35%, pending | pending | pending | not scored in this run |
| Reach | 25% (25 this run) | 90 | 70 | Carbon-X +20 |
| Risk | 20% (20 this run) | 65 | 50 | Carbon-X +15 |
| Agent interface | 10% (10 this run) | 35 | 75 | DeepSeek-V4-Flash-0731 +40 |
| Documentation and upkeep | 10% (10 this run) | 77 | 43 | Carbon-X +34 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **61 · C** | **62.4 · B** | |

## Facts side by side

| Fact | Carbon-X | DeepSeek-V4-Flash-0731 |
| --- | --- | --- |
| Kind | Open-weight model | Open-weight model |
| Vendor | Hugging Face (HuggingFaceBio) | DeepSeek |
| Hosted endpoint | no (local only) | no (local only) |
| Transports |  |  |
| Auth | None | None |
| Pricing | Free | Free |
| x402 | no | no |
| Licence | Apache-2.0 | MIT |
| Read-only variant documented | no | no |
| llms.txt | no | no |
| Last release | 2026-10-22 | 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 | 3/5 (4) | 2.5/5 (4) |

## Verdicts

**Carbon-X.** A DNA specialist cousin that another agent calls for variant-effect and sequence questions, with DNA kept on the machine. Hugging Face's Q4_K_M GGUF needs about 12 GB and Q8_0 about 19 GB, on llama.cpp b11742 or later. It isn't clinically validated, it isn't trained for tool calls or reasoning, and the card contradicts its own GGUF repository on llama.cpp support.

**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.

## Before you call either

### Carbon-X

1. Quickest start is `llama-server -hf HuggingFaceBio/Carbon-X-GGUF:Q8_0 -ngl 99 -c 40960 --jinja --chat-template-kwargs '{"enable_thinking": false}' --temp 0.6 --top-p 0.95 --top-k 20 --min-p 0`, on llama.cpp b11742 or later
2. With vLLM or Transformers pass trust_remote_code, and expect the tokenizer to fetch Qwen/Qwen3-4B-Base at a pinned revision on first load
3. Keep enable_thinking false and the card's sampling (temperature 0.6, top_p 0.95, top_k 20), the settings every reported result used
4. Keep DNA in files and pass sequences by name, compute positions and base changes in code and send them as context, the card says the model miscounts long sequences
5. Only A, C, G and T form 6-mers, so filter N and other IUPAC codes first or they become a single oov token
6. Strip the dna tags from answers if you need bare sequence, llama.cpp keeps them in the text
7. Cap max_tokens for next-base questions, long DNA generation is slow and degrades

### 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

## Questions

### Which is better for AI agents, Carbon-X or DeepSeek-V4-Flash-0731?

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


## For agents

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

## Other comparisons with Carbon-X or DeepSeek-V4-Flash-0731

- [Agents-A1-4B vs Carbon-X](https://www.anchorterminal.com/compare/agents-a1-4b-vs-carbon-x.md)
- [Agents-A1-4B vs DeepSeek-V4-Flash-0731](https://www.anchorterminal.com/compare/agents-a1-4b-vs-deepseek-v4-flash-0731.md)
- [Apertus v1.5 8B vs Carbon-X](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-carbon-x.md)
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- [Apodex-1.1-mini vs Carbon-X](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-carbon-x.md)
- [Apodex-1.1-mini vs DeepSeek-V4-Flash-0731](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-deepseek-v4-flash-0731.md)
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- [BigBang-v1 vs DeepSeek-V4-Flash-0731](https://www.anchorterminal.com/compare/bigbang-v1-vs-deepseek-v4-flash-0731.md)
- [Carbon-X vs Cosmos-Reason2-2B](https://www.anchorterminal.com/compare/carbon-x-vs-cosmos-reason2-2b.md)
- [Carbon-X vs Darwin-36B-Opus](https://www.anchorterminal.com/compare/carbon-x-vs-darwin-36b-opus.md)
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- [Carbon-X vs DiffusionGemma 26B A4B IT](https://www.anchorterminal.com/compare/carbon-x-vs-diffusiongemma-26b-a4b-it.md)
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