LFM3-1.7B-MLX-8bit
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LFM3-1.7B-MLX-bf16
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View details ↗LFM3-1.7B-NVFP4
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View details ↗LFM3-1.7B-ONNX
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View details ↗LFM3-Audio-2B
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View details ↗LFM3-Audio-2B-GGUF
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View details ↗LFM3-Audio-2B-MLX-bf16
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View details ↗LFM3-Omni-2B
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View details ↗LFM3-Omni-2B-GGUF
LiquidAILFM3-Omni-2B is an omni-modal model that understands text, images, video and audio, and answers in text and speech. It is built for on-device use. Recommended sampling: greedy decoding (temperature 0) for text output. For speech output, audio temperature 0.4 and audio repetition penalty 1.2. > [!NOTE] > Supported in llama.cpp b11960 (v0.8.0) and newer, including real-time voice conversations (with tool calls) on the `/v1/realtime` WebSocket API of `llama serve`.
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View details ↗LFM3-Omni-2B-MLX-4bit
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View details ↗LFM3-Omni-2B-MLX-8bit
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View details ↗LFM3-Omni-2B-MLX-bf16
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View details ↗LFM3-Omni-2B-ONNX
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View details ↗LFM3-VL-2B
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View details ↗LFM3-VL-2B-FP8
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View details ↗LFM3-VL-2B-GGUF
LiquidAIThe Q4_0 build in this repository is the Quantization-Aware Distillation (QAD) checkpoint, `LFM3-VL-2B-QAD-Q4_0.gguf`. It was trained to recover the accuracy lost to Q4_0 quantization.
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View details ↗LFM3-VL-2B-MLX-4bit
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View details ↗LFM3-VL-2B-MLX-5bit
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View details ↗LFM3-VL-2B-MLX-6bit
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View details ↗LFM3-VL-2B-MLX-8bit
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View details ↗LFM3-VL-2B-MLX-bf16
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View details ↗Liquid-Codec
LiquidAIThe repository includes the codec configuration and model implementation, so it can be loaded with `AutoModel`:
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View details ↗No matching models
Adjust provider, category or input/output filters. New models are added continuously.
COST EXPLORER
Great models. Clear costs.
Adjust monthly token usage to compare estimated API costs.
1 M = 1 million tokens · USD
Compares base text-token rates within the same channel
Compares base text-token rates within the same channel
Uses collected, comparable USD-per-million-token rates. Snapshots exclude cache discounts, tiers, extra reasoning output and taxes. Check current source prices.
MODEL HANDBOOK
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How should API prices be compared?+
Separate input, output and cache rates, then estimate the same workload. Image, audio and video rates may use items, duration or resolution rather than tokens.
Do open weights mean free commercial use?+
Not necessarily. Check each version’s license, commercial restrictions and policies. Self-hosting also incurs compute and maintenance costs.
Is the top-ranked model the best for me?+
Rankings depend on tasks, versions and methods. Compare accuracy, latency, reliability and costs on your own workload.