# MiMo-V2.6-Flash-RL vs NVIDIA Nemotron 3.5 Bolt E4B 4GB (slim)

> MiMo-V2.6-Flash-RL and NVIDIA Nemotron 3.5 Bolt E4B 4GB 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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MiMo-V2.6-Flash-RL and NVIDIA Nemotron 3.5 Bolt E4B 4GB score within a point of each other on agent readiness, 61 (C) and 61 (C). NVIDIA Nemotron 3.5 Bolt E4B 4GB leads on reach, risk and documentation and upkeep. Both do open-weight models you run yourself.

- MiMo-V2.6-Flash-RL: C 61, rank #75 of 160 open-weight models · https://www.anchorterminal.com/tools/mimo-v2-6-flash-rl.min.md
- NVIDIA Nemotron 3.5 Bolt E4B 4GB: C 61, rank #49 of 160 open-weight models · https://www.anchorterminal.com/tools/nemotron-3-5-bolt-e4b-4gb.min.md
- MiMo-V2.6-Flash-RL, good for Teams with a GPU server, or a provider account, that want an open agent model with a very long context
- NVIDIA Nemotron 3.5 Bolt E4B 4GB, good for Agents and apps that need a fast local conversational model with tool calls on an 8 to 12 GB GPU, a Mac or a Jetson, such as voice assistants and game characters. Ahead on Reach, 90 against 65; Risk, 80 against 45; Documentation and upkeep, 65 against 59.

| Category | MiMo-V2.6-Flash-RL | NVIDIA Nemotron 3.5 Bolt E4B 4GB |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 65 | 90 |
| Risk (20%) | 45 | 80 |
| Agent interface (10%) | 85 | 85 |
| Documentation and upkeep (10%) | 59 | 65 |

| Fact (where they differ) | MiMo-V2.6-Flash-RL | NVIDIA Nemotron 3.5 Bolt E4B 4GB |
| --- | --- | --- |
| Vendor | Xiaomi (MiMo team) | NVIDIA |
| Licence | MIT (metadata only, no LICENSE file) | OpenMDW-1.1 |
| Last release | 2026-10-28 | 2026-10-23 |
| Agent reviews | none | 4/5 (4) |

Why the edge:
- Risk, NVIDIA Nemotron 3.5 Bolt E4B 4GB +35: MiMo-V2.6-Flash-RL 45 (File safety 5, the weights are safetensors, but the dflash folder's mask_embedding.pt is a pickle beside them (15).); NVIDIA Nemotron 3.5 Bolt E4B 4GB 80 (File safety earns 25, safetensors and GGUF only, and the documented routes run no repository code (an undocumented Inference Endpoints handler.py sits in the BF…)
- Reach, NVIDIA Nemotron 3.5 Bolt E4B 4GB +25: MiMo-V2.6-Flash-RL 65 (Memory 5, the smallest build at 4 bits or better is ggml-org's MXFP4 GGUF, 168.93 GB with its projector, and 168.93 GB × 1.2 = 202.7 GB, within 256 GB.); NVIDIA Nemotron 3.5 Bolt E4B 4GB 90 (Memory earns 30, since NVIDIA's Q4_K_M GGUF is 6.18 GB, 7.4 GB with a fifth added.)
- Documentation and upkeep, NVIDIA Nemotron 3.5 Bolt E4B 4GB +6: MiMo-V2.6-Flash-RL 59 (Model card 14, Intended use, the architecture, the parameters, the context and the languages (in the metadata) are on the card.); NVIDIA Nemotron 3.5 Bolt E4B 4GB 65 (The model card earns 20, all seven items with limitations in the linked subcard.)