Deepseek V4 Flash 2-bit quant is the first model I can run locally that achieves 100% in this SQL benchmark

Reddit r/LocalLLaMA Models

Summary

A user reports that DeepSeek V4 Flash, running as a 2-bit quantized GGUF on dual RTX 3080s, is the first local model to score 100% on a real-world SQL benchmark, matching frontier models like Opus 4.7 and GPT-5.5.

I really like to use this one SQL benchmark when testing new models. I had another post some time ago with my benchmarks, but I decided to post a new one because of how well Deepseek did. I like the benchmark because it's quick to run, is pretty "real-world" and requires good reasoning to build the correct SQL queries and almost no frontier models can achieve 100%. My old post: https://www.reddit.com/r/LocalLLaMA/comments/1s9mkm1/benchmarked_18_models_that_i_can_run_on_my_rtx/ Benchmark with results from other models: https://sql-benchmark.nicklothian.com https://github.com/nlothian/llm-sql-benchmark My setup is dual 3080 20GB GPUs with 96GB RAM and 9800X3D. I managed to run Deepseek V4 Flash with a custom IQ2_M GGUF with some tensors grafted from antirez GGUF and running it on a modified ds4 engine from antirez, getting 300pp and 11-12tg. Mainline llama.cpp gives me only 100pp and 8tg or something like that. To my surprise, Deepseek is the first local model I can realistically run locally that actually did ALL tests correctly. The only models according to the benchmark website that could do this were Opus 4.7 and GPT-5.5. Results together with all my old benches: 25: Deepseek-v4-Flash-IQ2_M-grafted 🟩🟩🟩🟩🟩 🟩🟩🟩🟩🟩 🟩🟩🟩🟩🟩 🟩🟩🟩🟩🟩 🟩🟩🟩🟩🟩 24: unsloth/Qwen3.6-27B-MTP-GGUF:Q8_0 🟩🟩🟩🟩🟩 🟩🟩🟩🟩🟩 🟩🟩🟩🟩🟩 🟩🟩🟩🟩🟩 🟩🟩πŸŸ₯🟩🟩 24: unsloth/Qwen3.5-122B-A10B-GGUF:UD-Q4_K_XL 🟩🟩🟩🟩🟩 🟩🟩🟩🟩🟩 🟩🟩🟩🟩🟩 🟩🟩🟩πŸŸ₯🟩 🟩🟩🟩🟩🟩 23: unsloth/Qwen3.5-122B-A10B-GGUF:Q6_K 🟩🟩🟩🟩🟩 🟩🟩🟩🟩🟩 🟩🟩🟩🟩🟩 🟩🟩🟩πŸŸ₯🟩 πŸŸ₯🟩🟩🟩🟩 23: unsloth/Qwen3.5-27B-MTP-GGUF:UD-Q6_K_XL 🟩🟩🟩🟩🟩 🟩🟩🟩🟩🟩 🟩🟩🟩🟩🟩 🟩🟩🟩πŸŸ₯🟩 πŸŸ₯🟩🟩🟩🟩 23: DavidAU/Qwen3.6-40B-Claude-4.6-Opus-Deckard-Heretic-Uncensored-Thinking-NEO-CODE-Di-IMatrix-MAX-GGUF:Q4_K_M 🟩🟩🟩🟩🟩 🟩🟩🟩🟩🟩 🟩🟩πŸŸ₯🟩🟩 🟩🟩🟩πŸŸ₯🟩 🟩🟩🟩🟩🟩 23: unsloth/Qwen3.6-35B-A3B-GGUF:UD-Q8_K_XL 🟩🟩🟩🟩🟩 🟩🟩🟩🟩🟩 🟩🟩πŸŸ₯🟩🟩 🟩🟩🟩πŸŸ₯🟩 🟩🟩🟩🟩🟩 23: bartowski/Qwen_Qwen3.5-27B-GGUF:IQ4_XS 🟩🟩🟩🟩🟩 🟩🟩🟩🟩🟩 🟩🟩🟩🟩🟩 🟩🟩🟩πŸŸ₯🟩 πŸŸ₯🟩🟩🟩🟩 23: bartowski/Qwen_Qwen3.5-27B-GGUF:IQ3_XS 🟩🟩🟩🟩🟩 🟩🟩🟩🟩🟩 🟩🟩🟩🟩🟩 🟩🟩🟩πŸŸ₯🟩 πŸŸ₯🟩🟩🟩🟩 23: unsloth/Qwen3.5-122B-A10B-GGUF:UD-IQ3_XXS 🟩🟩🟩🟩🟩 🟩🟩🟩🟩🟩 🟩🟩🟩🟩🟩 🟩🟩🟩πŸŸ₯🟩 πŸŸ₯🟩🟩🟩🟩 23: h34v7/Jackrong-Qwopus3.5-27B-v3-GGUF:Q3_K_M 🟩🟩🟩🟩🟩 🟩🟩🟩🟩🟩 🟩🟩🟩🟩🟩 🟩🟩🟩πŸŸ₯🟩 πŸŸ₯🟩🟩🟩🟩 22: unsloth/Qwen3.5-35B-A3B-GGUF:UD-Q6_K_XL 🟩🟩🟩🟩🟩 🟩🟩🟩🟩🟩 🟩🟩πŸŸ₯🟩🟩 🟩🟩🟩πŸŸ₯🟩 πŸŸ₯🟩🟩🟩🟩 22: mradermacher/Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled-i1-GGUF:Q3_K_M 🟩🟩🟩🟩🟩 🟩🟩🟩🟩🟩 🟩🟩🟩🟩🟩 🟩πŸŸ₯🟩πŸŸ₯🟩 πŸŸ₯🟩🟩🟩🟩 22: Jackrong/Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled-v2-GGUF:Q4_K_M 🟩🟩🟩🟩🟩 🟩🟩🟩🟩🟩 🟩🟩🟩🟩🟩 🟩🟩πŸŸ₯πŸŸ₯🟩 πŸŸ₯🟩🟩🟩🟩 21: unsloth/Qwen3.6-27B-MTP-GGUF:UD-Q6_K_XL 🟩🟩🟩🟩🟩 🟩🟩🟩🟩🟩 🟩πŸŸ₯🟩🟩🟩 🟩🟩🟩πŸŸ₯🟩 🟩🟨πŸŸ₯🟩🟩 21: unsloth/MiniMax-M2.7-GGUF:UD-IQ3_XXS 🟩🟩🟩🟩🟩 🟩🟩🟩🟩🟩 🟩🟩🟩🟩🟩 🟩🟩🟩πŸŸ₯🟩 πŸŸ₯πŸŸ₯πŸŸ₯🟩🟩 21: unsloth/NVIDIA-Nemotron-3-Super-120B-A12B-GGUF:UD-Q4_K_S 🟩🟩🟩🟩🟩 🟩🟩🟩🟩🟩 🟩🟩🟩🟩🟩 🟩🟩🟩🟨πŸŸ₯ πŸŸ₯🟨🟩🟩🟩 20: unsloth/Qwen3-Coder-Next-GGUF:UD-Q5_K_XL 🟩🟩🟩🟩🟨 🟩🟩🟩🟩🟩 🟩🟩🟨🟩🟩 🟩🟩🟩πŸŸ₯🟨 πŸŸ₯🟩🟩🟩🟩 20: unsloth/gemma-4-31B-it-qat-GGUF:UD-Q4_K_XL 🟩🟩🟩🟩🟩 🟩🟩🟩🟩🟩 πŸŸ₯🟩🟩🟩🟩 🟨🟩🟩πŸŸ₯🟩 πŸŸ₯🟩🟩πŸŸ₯🟩 20: unsloth/Qwen3.6-35B-A3B-GGUF:UD-Q6_K_XL 🟩🟩🟩🟩🟩 🟩🟩🟩🟩🟩 🟩🟩πŸŸ₯🟩🟩 🟩🟩🟩πŸŸ₯🟩 πŸŸ₯πŸŸ₯πŸŸ₯🟩🟩 20: bartowski/Qwen_Qwen3.5-397B-A17B-GGUF:IQ1_M 🟩🟩🟩🟩🟩 🟩🟩🟩🟩🟩 🟩🟩πŸŸ₯🟩🟩 🟩🟩🟩πŸŸ₯🟩 πŸŸ₯🟨πŸŸ₯🟩🟩 20: unsloth/gemma-4-26B-A4B-it-GGUF:UD-Q6_K_XL 🟩🟩🟩🟩🟩 🟩🟩🟩🟩🟩 🟩🟩🟩🟩🟩 🟩🟩🟩πŸŸ₯πŸŸ₯ 🟨πŸŸ₯🟩πŸŸ₯🟩 20: mradermacher/Qwen3.5-35B-A3B-Claude-4.6-Opus-Reasoning-Distilled-i1-GGUF:Q6_K 🟩🟩🟩🟩🟩 🟩🟩🟩🟩🟩 🟩🟩πŸŸ₯🟩🟩 πŸŸ₯🟩🟩πŸŸ₯🟩 πŸŸ₯πŸŸ₯🟩🟩🟩 19: unsloth/gemma-4-31B-it-GGUF:Q4_K_M 🟩🟩🟩🟩🟩 🟩🟩🟩🟩🟩 🟩🟩🟩πŸŸ₯🟩 🟨🟩🟩🟨🟩 πŸŸ₯πŸŸ₯🟩πŸŸ₯🟩 19: unsloth/gemma-4-E4B-it-GGUF:UD-Q8_K_XL 🟩🟩🟩🟩🟩 🟩🟩🟩🟩🟩 🟩🟩🟩πŸŸ₯🟩 🟩🟩🟩πŸŸ₯🟩 πŸŸ₯πŸŸ₯πŸŸ₯πŸŸ₯🟩 19: Goldkoron/Qwen3.5-397B-A17B-REAP35:IQ2_XS_Gv2 🟩🟩🟩🟩🟩 🟩🟩🟩🟩🟩 πŸŸ₯🟩🟩🟩🟩 🟩🟩🟩πŸŸ₯🟩 πŸŸ₯🟩πŸŸ₯πŸŸ₯πŸŸ₯ 19: unsloth/GLM-4.7-Flash-GGUF:UD-Q6_K_XL 🟩🟩🟩🟩🟩 🟩🟩🟩🟩🟩 🟩🟩πŸŸ₯🟩🟩 🟩🟩🟩πŸŸ₯🟨 πŸŸ₯🟨🟩πŸŸ₯🟩 18: unsloth/GLM-4.5-Air-GGUF:Q5_K_M 🟩🟩🟩🟩🟩 🟩🟩🟩🟩🟩 🟩🟩πŸŸ₯🟩🟩 πŸŸ₯🟩🟩πŸŸ₯🟩 🟨🟨πŸŸ₯🟩🟨 18: bartowski/nvidia_Nemotron-Cascade-2-30B-A3B-GGUF:Q6_K_L 🟩🟩🟩🟩🟩 🟩🟩🟩🟩🟩 🟩🟩🟨🟩🟩 🟩🟩🟩πŸŸ₯🟩 🟨🟨πŸŸ₯🟨🟨 17: Jackrong/Qwopus3.5-9B-v3-GGUF:Q8_0 🟩🟩🟩🟩🟩 🟩🟩🟩🟩🟩 🟩πŸŸ₯πŸŸ₯🟩🟩 πŸŸ₯🟩πŸŸ₯πŸŸ₯πŸŸ₯ πŸŸ₯🟩🟩🟩🟨 16: unsloth/Qwen3-Coder-Next-GGUF:UD-Q4_K_XL 🟩🟩🟩🟩🟨 🟩🟩🟩🟩🟩 🟩🟩🟨🟩🟩 πŸŸ₯🟨🟩πŸŸ₯🟨 πŸŸ₯🟨🟩🟨🟩 16: byteshape/Devstral-Small-2-24B-Instruct-2512-GGUF:IQ3_S 🟩🟩🟩🟩🟩 🟩🟩🟩🟩🟩 πŸŸ₯🟩🟨🟩🟩 🟩🟩🟨πŸŸ₯🟨 🟨🟨πŸŸ₯🟨🟩 16: mradermacher/Qwen3.5-9B-Claude-4.6-HighIQ-THINKING-i1-GGUF:Q6_K 🟩🟩🟩🟩🟩 🟩🟩🟩🟩🟩 🟩🟩🟨πŸŸ₯🟩 πŸŸ₯🟩πŸŸ₯πŸŸ₯🟨 πŸŸ₯🟩πŸŸ₯🟩🟨 14: mradermacher/Qwen3.5-9B-Claude-4.6-HighIQ-INSTRUCT-i1-GGUF:Q6_K 🟩🟩🟩🟩🟩 🟩🟩🟩🟩🟩 πŸŸ₯🟩πŸŸ₯🟩🟩 🟩🟨πŸŸ₯πŸŸ₯🟨 🟨🟨πŸŸ₯🟨🟨 14: unsloth/GLM-4.6V-GGUF:Q3_K_S 🟩🟩🟩🟩🟩 🟩🟩🟩🟩🟩 πŸŸ₯🟩🟨🟨🟩 πŸŸ₯🟩🟩🟨🟨 🟨🟨🟨🟨🟨 5: bartowski/Tesslate_OmniCoder-9B-GGUF:Q6_K_L 🟨🟨🟨🟨🟨 🟨🟨🟨🟩🟩 🟩🟨🟨🟩🟨 🟨🟨🟩🟨🟨 🟨🟨🟨🟨🟨 5: unsloth/Qwen3.5-9B-GGUF:UD-Q6_K_XL 🟨🟨🟨🟨🟨 🟨🟨🟨🟩🟩 🟨🟩🟨🟨🟩 🟨🟩🟨🟨🟨 🟨🟨🟨🟨🟨 Note: unsloth/Qwen3.5-122B-A10B-GGUF:UD-Q4_K_XL is most likely a fluke. Q6_K doesn't achieve 24/25, it's just lucky rounding for this Q4 quant I suppose.
Original Article

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