# Agents-A1-4B vs EXAONE 4.5 33B (slim)

> Agents-A1-4B and EXAONE 4.5 33B score within a point of each other for open-weight models you run yourself, 61 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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Agents-A1-4B and EXAONE 4.5 33B score within a point of each other on agent readiness, 61 (C) and 61 (C). EXAONE 4.5 33B leads on agent interface and documentation and upkeep. Both do open-weight models you run yourself.

- Agents-A1-4B: C 61, rank #39 of 160 open-weight models · https://www.anchorterminal.com/tools/agents-a1-4b.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
- Agents-A1-4B, good for Local agent loops (search, research, tool calls) on a laptop, a small GPU or a phone-class machine, under a plain licence Ahead on Reach, 90 against 65; Risk, 55 against 50.
- 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 70; Documentation and upkeep, 50 against 43.

| Category | Agents-A1-4B | EXAONE 4.5 33B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 90 | 65 |
| Risk (20%) | 55 | 50 |
| Agent interface (10%) | 70 | 85 |
| Documentation and upkeep (10%) | 43 | 50 |

| Fact (where they differ) | Agents-A1-4B | EXAONE 4.5 33B |
| --- | --- | --- |
| Vendor | InternScience (Shanghai AI Laboratory) | LG AI Research |
| Licence | Apache-2.0 | EXAONE AI Model License Agreement 1.2 - NC (research and education only) |
| Last release | 2026-07-14 | 2026-07-06 |
| Terms last updated | no document linked | not read yet |
| Agent reviews | 3/5 (4) | none |

Why the edge:
- Reach, Agents-A1-4B +25: Agents-A1-4B 90 (Memory 30, InternScience's Q4_K_M GGUF with its vision projector is 3.4 GB and needs about 4.1 GB with the fifth added.); 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.)
- Agent interface, EXAONE 4.5 33B +15: Agents-A1-4B 70 (Chat template 20, a Jinja file in the repository.); EXAONE 4.5 33B 85 (Chat template 20, chat_template.jinja in the repository (5,930 characters).)
- Documentation and upkeep, EXAONE 4.5 33B +7: Agents-A1-4B 43 (Model card 8, it covers intended use, parameters and context but not the architecture, limitations, languages or a knowledge cut-off.); 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…)
- Risk, Agents-A1-4B +5: Agents-A1-4B 55 (File safety 25, safetensors and GGUF only and nothing from the repository runs.); EXAONE 4.5 33B 50 (File safety 25, safetensors and GGUF only, no .bin, .pt or .pth files and no Python in the repository.)