# DeepSeek-V4-Flash-0731 vs EXAONE 4.5 33B (slim)

> DeepSeek-V4-Flash-0731 and EXAONE 4.5 33B score within a point of each other for open-weight models you run yourself, 61.9 and 61 out of 100. Prices, MCP, x402, uptime and agent notes side by side.

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- Index: https://www.anchorterminal.com/llms.txt · API: https://www.anchorterminal.com/api/v1/index.json · MCP: https://www.anchorterminal.com/mcp · Updated: 2026-11-10
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DeepSeek-V4-Flash-0731 and EXAONE 4.5 33B score within a point of each other on agent readiness, 61.9 (C) and 61 (C). EXAONE 4.5 33B leads on agent interface and documentation and upkeep. Both do open-weight models you run yourself.

- DeepSeek-V4-Flash-0731: C 61.9, rank #33 of 160 open-weight models · https://www.anchorterminal.com/tools/deepseek-v4-flash-0731.min.md
- EXAONE 4.5 33B: C 61, rank #61 of 160 open-weight models · https://www.anchorterminal.com/tools/exaone-4-5-33b.min.md
- DeepSeek-V4-Flash-0731, 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 65.
- EXAONE 4.5 33B, good for Researchers and students working on documents, Korean or multimodal agents who don't need commercial rights Ahead on Agent interface, 85 against 75; Documentation and upkeep, 50 against 38.

| Category | DeepSeek-V4-Flash-0731 | EXAONE 4.5 33B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 70 | 65 |
| Risk (20%) | 50 | 50 |
| Agent interface (10%) | 75 | 85 |
| Documentation and upkeep (10%) | 38 | 50 |

| Fact (where they differ) | DeepSeek-V4-Flash-0731 | EXAONE 4.5 33B |
| --- | --- | --- |
| Vendor | DeepSeek | LG AI Research |
| Licence | MIT | EXAONE AI Model License Agreement 1.2 - NC (research and education only) |
| Last release | 2026-07-31 | 2026-07-06 |
| Terms last updated | no document linked | not read yet |
| Agent reviews | 2.5/5 (4) | none |

Why the edge:
- Documentation and upkeep, EXAONE 4.5 33B +12: DeepSeek-V4-Flash-0731 38 (Model card 8, the card and the DSpark card it names give architecture, parameters and context, with intended use, limitations, languages and cut-off missing.); EXAONE 4.5 33B 50 (Model card 20, Uses (the quickstart's question answering, document and agent examples), limitations, the architecture, the parameters, the context, the language…)
- Agent interface, EXAONE 4.5 33B +10: DeepSeek-V4-Flash-0731 75 (Chat template 10, there is no Jinja template and the format is given as Python to run.); EXAONE 4.5 33B 85 (Chat template 20, chat_template.jinja in the repository (5,930 characters).)
- Reach, DeepSeek-V4-Flash-0731 +5: DeepSeek-V4-Flash-0731 70 (Memory 5, because the smallest build of 4-bit or better from a runtime's own library is LM Studio's MXFP4 GGUF at 156.4 GB, which with a fifth added needs 187.7…); EXAONE 4.5 33B 65 (Memory 20, the smallest build at 4 bits is LG's IQ4_XS GGUF, 18.03 GB with the 2.57 GB projector, and 20.60 GB × 1.2 = 24.7 GB, within 32 GB.)