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wrldsuksgo2mars
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Model Details
Model Provider
wrldsuksgo2mars
Model Tree
deepseek-ai/DeepSeek-V4-Flash-0731
Input Modalities
Output Modalities
Supported Functionality
The quantization used 1,426 prompts totaling 1,081,027 tokens. The corpus emphasizes English and Chinese and combines code, multilingual general knowledge, worked math, reasoning/termination, and structured tool-call examples. Code spans Python, C++, CUDA, C, Rust, and a broader mix of systems and application languages.
This is a direct single-pass mixed quantization, not a blend of separately
generated K2 and K3 models. Every projection is encoded at K2, scored by its
Hessian-weighted relative error times natural gate-squared mass, and the
highest-scoring projections are immediately re-encoded at K3 within a fixed
gate:up:down = 3:5:8 budget. The mixed block is replayed before advancing,
so every later layer is calibrated against the real mixed prefix.
Natural top-6 router selections supplied expert activations. Experts below the 1,024-row target received deterministic candidates from router ranks 7–12, with any remaining deficit represented by an explicitly counted isotropic Hessian residual. The three dSpark blocks were replayed from a 327,680-anchor stratified sample with all five proposal rows issued jointly.
All 43 target blocks and all three dSpark blocks passed their independent projection audits. The final checkpoint contains 35,328 routed projections: 3,302 of 33,024 target projections and 461 of 2,304 dSpark projections use K3.
These results use one RTX 6000 Blackwell coordinator plus four DGX Sparks with TP4 experts, the balanced FP8-KV profile, adaptive dSpark, greedy decoding, and the same current DS4RT build for both artifacts.
| Measurement | This model | K2 calibrated v1 control |
|---|
| Code-shaped C1 decode, five-run median | 144.60 tok/s | 150.51 tok/s |
| Code-shaped C4 aggregate decode, five-run median | 259.98 tok/s | 259.98 tok/s |
| Fresh exact 8K prefill, three-run median | 2,235.61 tok/s | 2,305.24 tok/s |
| Adaptive dSpark accepted drafts | 62.72% | 64.90% |
| Tool Eval Bench 2.3.2, 69 scenarios | 88/100 (121/138) | 90/100 (124/138) |
The exact-output C4 gate passed every warmup and timed lane with zero runtime kernel captures. Tool Eval completed without request or backend errors.
The checkpoint follows the source architecture: 43 target blocks, 4,096 hidden size, 256 routed experts with top-6 routing, one shared expert, three integrated dSpark blocks, and a configured maximum position length of 1,048,576 tokens.
An inference runtime must support DeepSeek V4, the EXL3 MCG codebook, and projection-mixed K2/K3 trellises. This remains a standard, unsliced Hugging Face sharded checkpoint with every expert present. Use the tokenizer and prompt formatting documented by the original model.