Model overview
**Requires the custom llama.cpp patch in this repository. Stock llama.cpp, Ollama and LM Studio have NOT been validated with this new `aliceai` architecture. Do not expect this file to work by simply importing it into an unmodified app.** This is a community conversion, not an official Yandex release. It is an 80B-parameter MoE **Base completion model**, not an instruction-tuned assistant. MTP is **not implemented**; the source MTP module is omitted. No training, fine-tuning, distillation or additional alignment was performed. - `AliceAI-Foundation-80B-A3B-Base-Q4_K_M.gguf`: **48,421,862,304 bytes (45.10 GiB)**, 1,167 tensors, approximately 4.86 bits/weight. - Converted directly from the original BF16 source, **not requantized from MLX Q4**. - Source: yandex/AliceAI-Foundation-80B-A3B-Base, revision `b7984f62fd212535d2de9094bfeba23de58cd7c8`. - Runtime base: ggml-org/llama.cpp, commit `7ab4ee7baad2d920464cbacfad4f4b07cf111fd2`, plus `aliceai-llama.cpp.patch`. - Q4_K_M uses mixed tensor precision, including Q6_K. In addition, **72 small KDA projection tensors use Q5_0**, because their width of 128 cannot use 256-element K-quant blocks. Norms, router weights, depth-residual scores and convolution weights retain FP32. This is not an all-tensors-exactly-4bit model. - The inherited GGUF display name is `Source`; identify the model by its file name and use `--alias AliceAI-80B-A3B-Q4` if desired. This label does not affect weights.
Key features
特点摘要待依据来源补齐，不凭模型名称推断能力。
Limitations & considerations
Sources are insufficient to establish specific limitations. Verify task performance, latency, data policies, licensing and version lifecycle.
Source prices & cost analysis
Prices vary by channel, region and configuration. Channel quotes are listed independently and are not treated as a single official provider price.
| Source / channel | Input | Output | Billing unit | Collected at |
|---|---|---|---|---|
| No verified prices yet. Check the source channel. | ||||
Estimate monthly base token costs
Estimates exclude cache discounts, tiered pricing, multimodal surcharges, web search, taxes and additional reasoning output.
Public benchmarks & run configuration
暂无已采集的可核验公开评分。模型未上榜不代表能力较低。
View full indexed rankings →Frequently asked questions
Do open weights permit free commercial use?
Not necessarily. Check the version license, commercial conditions and usage policies. Self-hosting incurs compute and maintenance costs.
Are these real-time billing prices?
These are timestamped source snapshots, not live billing prices. Check the channel for current versions, regions, discounts and billing methods.
Sources & traceability
许可证：apache-2.0。模型介绍与第三方评测均以原来源的具体版本和方法为准。