# IBM发布三款高效非推理模型Granite 4.1，采用Apache 2.0开源许可

- 来源：Artificial Analysis (@ArtificialAnlys)
- 发布时间：2026-04-29 23:06
- AIHOT 分数：63
- AIHOT 链接：https://aihot.virxact.com/items/cmok6zuki00a6slgczp918uca
- 原文链接：https://x.com/ArtificialAnlys/status/2049505499377193156

## AI 摘要

IBM发布了三款采用Apache 2.0许可的Granite 4.1开源模型（30B、8B、3B）。其核心特点是极高的令牌效率，例如8B模型运行智能指数仅需4M输出令牌，远低于同类模型。在开放性指数上，三款模型均获得61分，领先多数同行。但高效率也带来了智能指数的相对折衷，其得分低于Qwen3.5、Gemma 4等竞品。不过，与上一代Granite 4.0系列相比，新模型的智能表现仍有提升。该系列模型拥有128K令牌的上下文窗口，主要面向企业和边缘部署，可通过WandB、Replicate和Hugging Face获取。

## 正文

IBM has released three new non-reasoning Granite 4.1 models （30B， 8B， 3B） as open weights under Apache 2.0. All three are notably token-efficient relative to peer non-reasoning models， with the 8B standing out for its token efficiency relative to intelligence

@IBM has released three new instruct models in the Granite 4.1 family： Granite 4.1 30B （15 on the Intelligence Index）， Granite 4.1 8B （12）， and Granite 4.1 3B （9）. The release continues IBM's focus on small， efficient， and open models for enterprise and edge deployment， alongside the existing Granite 4.0 Nano family （1B and 350M variants released in October 2025）. The Intelligence Index is the Artificial Analysis synthesis metric incorporating 10 evaluations covering agentic tasks， coding， and scientific reasoning.

Key benchmarking results：

➤ All three Granite 4.1 models score 61 on the Artificial Analysis Openness Index， standing out among peer open weights non-reasoning models. This is driven by full open weights under Apache 2.0 plus partial disclosures across pre-training data， post-training data， and training methodology. Granite 4.1 sits well above peers like Qwen3.5 （39）， Gemma 4 （39） and GLM-4.7-Flash （44）， and represents a meaningful improvement over the Granite 4.0 family （56）， driven by stronger methodology disclosure. Olmo 3.1 and K2 Think V2 （both 89） remain leaders as the most 'open' models.

➤ Granite 4.1 8B uses just 4M output tokens to run the Intelligence Index. This is ~20x fewer than Qwen3.5 9B （78M tokens）， ~3x fewer than Ministral 3 8B （13M）， and ~2x fewer than Gemma 4 E4B （8M）. The pattern holds across the family： Granite 4.1 30B uses 4.6M output tokens （vs 7M for Gemma 4 31B and 25M for Qwen3.5 27B）， and Granite 4.1 3B uses 2.7M.

➤ Token efficiency comes at the cost of intelligence relative to peer non-reasoning models. Granite 4.1 30B （15） trails leading peers like Qwen3.5 27B （37） and Gemma 4 31B （32）. Granite 4.1 8B （12） trails Ministral 3 8B （15） and Gemma 4 E4B （15）. Granite 4.1 3B （9） trails Gemma 4 E2B （12）.

➤ Granite 4.1 30B and 3B both gain on the Intelligence Index over their Granite 4.0 predecessors. Granite 4.1 30B （15） gains 4 points over Granite 4.0 H Small （32B / 9B active， 11）， with the largest gains in tool use （τ2-Bench： 42% vs 17%） and agentic tasks （GDPval-AA： 493 vs 344 Elo）. Granite 4.1 3B （9） gains 1 point over Granite 4.0 Micro （8）.

Other information：

➤ License： Apache 2.0 （open weights， permissive commercial use） ➤ Context window： 128K tokens ➤ Availability： Granite 4.1 8B is available via @WandB （$0.05/$0.1 per 1M input/output tokens） and @replicate. Weights for all three models are available via @huggingface.