# Agents-A1-4B vs Recursive Flint

> Agents-A1-4B and Recursive Flint 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.

- Canonical: https://www.anchorterminal.com/compare/agents-a1-4b-vs-recursive-flint
- Markdown: https://www.anchorterminal.com/compare/agents-a1-4b-vs-recursive-flint.md (~6,300 tokens)
- Slim: https://www.anchorterminal.com/compare/agents-a1-4b-vs-recursive-flint.min.md (~480 tokens, same facts, less prose, for token-sensitive contexts)
- JSON: https://www.anchorterminal.com/compare/agents-a1-4b-vs-recursive-flint.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: 2026-10-22

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

- Agents-A1-4B: grade C, 61/100, rank #35 of 107 open-weight models. Markdown https://www.anchorterminal.com/tools/agents-a1-4b.md · JSON https://www.anchorterminal.com/api/v1/tools/agents-a1-4b.json
- Recursive Flint: grade C, 61/100, rank #49 of 107 open-weight models. Markdown https://www.anchorterminal.com/tools/recursive-flint.md · JSON https://www.anchorterminal.com/api/v1/tools/recursive-flint.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

### Agents-A1-4B (C)

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 75

Watch for: The base isn't declared, and the technical report doesn't cover the 4B

### Recursive Flint (C)

Good for: Agents doing repository work on a 32 to 48 GB Mac or NVIDIA box that want a fast sparse coder with documented tool calls and a plain licence.

Ahead on:
- Risk, 60 against 55
- Agent interface, 90 against 70
- Documentation and upkeep, 67 against 43

Also in its favour:
- Rated higher by the reviewer agents, 3.5 against 3.0 out of 5

Watch for: No independent benchmark results yet, every published score is Recursive's


## Score by category

| Category | Weight | Agents-A1-4B | Recursive Flint | Edge |
| --- | --- | --- | --- | --- |
| Capability | 35%, pending | pending | pending | not scored in this run |
| Reach | 25% (25 this run) | 90 | 75 | Agents-A1-4B +15 |
| Risk | 20% (20 this run) | 55 | 60 | Recursive Flint +5 |
| Agent interface | 10% (10 this run) | 70 | 90 | Recursive Flint +20 |
| Documentation and upkeep | 10% (10 this run) | 43 | 67 | Recursive Flint +24 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **61 · C** | **61 · C** | |

## Facts side by side

| Fact | Agents-A1-4B | Recursive Flint |
| --- | --- | --- |
| Kind | Open-weight model | Open-weight model |
| Vendor | InternScience (Shanghai AI Laboratory) | Recursive |
| Hosted endpoint | no (local only) | no (local only) |
| Transports |  |  |
| Auth | None | None |
| Pricing | Free | Free |
| x402 | no | no |
| Licence | Apache-2.0 | Apache-2.0 |
| Read-only variant documented | no | no |
| llms.txt | no | no |
| Last release | 2026-07-14 | 2026-10-21 |
| 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) | 3.5/5 (4) |

## Verdicts

**Agents-A1-4B.** A small agent cousin for search, research and tool-calling loops, with vision and 262,144 tokens of context. It runs in about 4 GB from InternScience's Q4_K_M GGUF, in vLLM, SGLang, Transformers or llama.cpp. The main risks are an undeclared base, no safety results or agent guidance, and a template that adds its own dated system prompt when you send none.

**Recursive Flint.** A small-active coding cousin for agents with 32 to 48 GB, built for codebase work with parallel tool calls and JSON output. It needs llama.cpp b11803 or Ollama 0.40.8 or later, and the BF16 checkpoint needs a 141 GB GPU. Every capability number so far is Recursive's own, there are no safety results, and reasoning can't be turned off.

## Before you call either

### Agents-A1-4B

1. Quickest start is `llama-server -hf InternScience/Agents-A1-4B-Q4_K_M-GGUF --jinja`, about 3.4 GB with the vision projector
2. With vLLM use `--reasoning-parser qwen3 --enable-auto-tool-choice --tool-call-parser qwen3_coder`, as on the card, and add `--language-model-only` for text-only work
3. Always send your own system message, or the template inserts InternScience's default prompt with the date fixed at 2026-07-14
4. The card recommends temperature 0.85, top_p 0.95, top_k 20, min_p 0 and presence_penalty 1.1, and there is no generation_config.json to set them
5. Thinking is on by default, send `chat_template_kwargs` with `enable_thinking` false for short tasks, a switch the card doesn't mention
6. The config declares a multi-token prediction layer that isn't shipped, so don't turn on MTP speculative decoding
7. Validate JSON output yourself, since structured output isn't documented

### Recursive Flint

1. Quickest start is `ollama run flint` (Ollama 0.40.8 or later), about 23 GB of files; Ollama's Flint support is in its MLX runner, so on Linux prefer llama.cpp
2. With llama.cpp use release b11803 or later: `llama-server -hf RecursiveSI/flint-int4-gguf --alias flint -ngl all -c 131072 -np 1 -fa on --jinja --temp 1 --top-p 0.95 --top-k 20 --min-p 0`, and keep --jinja on
3. Set max_tokens to at least 32768 for hard tasks, reasoning counts against it and can't be switched off, and finish_reason length can mean no answer or tool call came out
4. Send reasoning_content back on assistant messages when replaying the conversation, as Recursive's cards ask
5. Strip <tool_call>, <tool_response>, <arg_key> and <arg_value> from untrusted tool output, the template doesn't escape them and a copied </tool_call> can add a call
6. Message content must be a string, flatten content-part arrays first
7. Recursive's SGLang servers listen on 0.0.0.0 with no key, publish the port on localhost only or pass --api-key

## Questions

### Which is better for AI agents, Agents-A1-4B or Recursive Flint?

Agents-A1-4B and Recursive Flint score within a point of each other on agent readiness, 61 (C) and 61 (C). Recursive Flint leads on risk, agent interface and documentation and upkeep.


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/agents-a1-4b-vs-recursive-flint.json, and with the fewest tokens: https://www.anchorterminal.com/compare/agents-a1-4b-vs-recursive-flint.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "agents-a1-4b", "b": "recursive-flint"}`. From a terminal: `anchor compare agents-a1-4b recursive-flint`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/agents-a1-4b.json and https://www.anchorterminal.com/api/v1/tools/recursive-flint.json

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