qwen3.8-27b-unc-fp8
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From language to images, open weights to APIs. Understand capabilities and compare real costs.
Find the right engine for your next idea.
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Novel smartness-first architecture combining: - DeepSeek V4.1-Flash CED + CSA2 + Engram + Single-Pass mHC + DSpark - Looped decoder (recurrent depth) + Mixture-of-Recursions routing - 15B total, ~2-3.5B active, 1M context staged See ARCHITECTURE.md for full spec. Target: frontier reasoning per active param on SWE-bench / Terminal-Bench / DeepSWE.
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Note that the model weights are saved in FP16. This type can be changed when the model is loaded using the `compute_type` option in CTranslate2.
Note that the model weights are saved in FP16. This type can be changed when the model is loaded using the `compute_type` option in CTranslate2.
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Adjust provider, category or input/output filters. New models are added continuously.
Adjust monthly token usage to compare estimated API costs.
Uses collected, comparable USD-per-million-token rates. Snapshots exclude cache discounts, tiers, extra reasoning output and taxes. Check current source prices.
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.
Not necessarily. Check each version’s license, commercial restrictions and policies. Self-hosting also incurs compute and maintenance costs.
Rankings depend on tasks, versions and methods. Compare accuracy, latency, reliability and costs on your own workload.