Alibaba has released Qwen3 Next 80B: an open weights hybrid reasoning model that achieves DeepSeek V3.1-level intelligence with only 3B active parameters Key takeaways: 💡 Novel architecture: First model to introduce @Alibaba_Qwen's ‘Qwen3-Next’ foundation models, with several key architecture decisions such as a hybrid attention mechanism of Gated DeltaNet and Gated Attention, and high sparsity with a 3.8% active parameters share, compared to 9.4% for Qwen3 235B 🧠 Intelligence: Qwen3 Next 80B (Reasoning) scores 54 on the Artificial Analysis Intelligence Index, placed alongside DeepSeek V3.1 (Reasoning). The non-reasoning variant scores 45, in line with gpt-oss-20B and Llama Nemotron Super 49B v1.5 (Reasoning) 💲 Pricing model: Per token pricing on @alibaba_cloud is $0.5/$6 per 1M input/output tokens for reasoning and $0.5/$2 for the non-reasoning variant. This compares to higher prices for Qwen3 235B 2507 of $0.7/$8.4 with reasoning and $0.7/$2.8 without - a ≥25% reduction depending on workloads ⚙️ Model details: The model has a native context window of 256k tokens and is text-only, with no multimodal inputs or outputs. At only 80B parameters at FP8 the model fits on a single H200 GPU

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DeepSeek launches V3.1, unifying V3 and R1 into a hybrid reasoning model with an incremental increase in intelligence Incremental intelligence increase: Initial benchmarking results for DeepSeek V3.1 show Artificial Analysis Intelligence Index of 60 in reasoning mode, up from the R1’s score of 59. In non-reasoning mode, V3.1 achieves a score of 49, a greater increase from the earlier V3 0324 score of 44. This leaves V3.1 (reasoning) behind Alibaba’s latest Qwen3 235B 2507 (reasoning) - DeepSeek has not taken back the lead. Hybrid reasoning: @deepseek_ai has moved to a hybrid reasoning model for the first time - supporting both reasoning and non-reasoning modes. DeepSeek’s move to a unified hybrid reasoning model mimics the approach taken by OpenAI, Anthropic and Google. It is interesting to note, however, that Alibaba recently abandoned their the hybrid approach they favored for Qwen3 with their separate releases of Qwen3 2507 reasoning and instruct models. Function calling / tool use: While DeepSeek claims improved function calling for the model, DeepSeek V3.1 does not support function calling when in reasoning mode. This is likely to substantially limit its ability to support agentic workflows with intelligence requirements, including in coding agents. Token usage: DeepSeek V3.1 scores incrementally higher in reasoning mode than DeepSeek R1, and uses slightly fewer tokens across the evals we use for Artificial Analysis Intelligence Index. In non-reasoning mode, it uses slightly more tokens than V3 0324 - but still several times fewer than in its own reasoning mode. API: DeepSeek’s first party API now serves the new DeepSeek V3.1 model on both their chat and reasoning endpoints - simply changing whether the end thinking </think> token is provided to the model in the chat template to control whether the model will reason. Architecture: DeepSeek V3.1 is architecturally identical to prior V3 and R1 models, with 671B total parameters and 37B active parameters. Implications: We would advise caution in making any assumptions about what this release implies about DeepSeek’s progress toward a future model referred to in rumors as V4 or R2. We note that DeepSeek previously released the final model built on their V2 architecture on December 10 2024, just two weeks before releasing V3.