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Best local models for document Q&A (October 2026)

Ranked for local document Q&A: capability (Artificial Analysis, BenchLeader), whether it fits 24 GB-512 GB hardware, license, runtime maturity. Nulls = no primary source found.

Last updated Oct 24, 2026. Fields tagged unverified lack a primary source. "No published figure yet" means we found no source, and we don't guess. Spark fit is estimated from published memory sizes, not tested on Spark hardware. Ollama listings may be cloud-only tags; check this for Kimi K3 and DeepSeek V4.1 before pulling.

Spark configs: single 路 dual 路 quad 路 DGX Spark hub

Top 10

#ModelMakerReleasedArchitecture / paramsContextLicenseMemoryRuns onWhy ranked here
1GLM-5.3-FlashZ.ai (Zhipu)2026-08-25MoE, hybrid sparse+linear attention, native multimodal (image/video)
320B total / 18B active
no published figure yet unverifiedMITBF16/native: ~306 GiB (Yotta Labs)
FP8: no published figure yet
Q8: no published figure yet
Q4: no published figure yet
LLMCheck: needs a 128 GB Mac at 3-bit in llama.cpp
Single Spark (128GB): Yes at ~3-bit (inferred from LLMCheck 128 GB Mac note) unverified
Dual Spark (256GB): Yes at ~4-bit (inferred) unverified
Quad Spark (~512GB): Yes, near-full precision fits (inferred) unverified
24GB GPU: No
128GB Mac / Strix: Yes at 3-bit (LLMCheck)
Best capability that actually fits a 128-512 GB box, MIT license, mainstream llama.cpp support. The sweet spot for Spark owners.
Details 路 Hugging Face
2Qwen3.8-27BAlibaba Qwen2026-08-05Dense, image+video input
27B (27.8B per HF) total / 27B active
262,144 native, extensible to ~1MApache-2.0BF16/native: ~54 GB (Yotta Labs)
FP8: no published figure yet
Q8: no published figure yet
Q4: ~16 GB (Yotta Labs; 24 GB GPU class)
Single Spark (128GB): Yes, BF16 fits
Dual Spark (256GB): Yes
Quad Spark (~512GB): Yes
24GB GPU: Yes
128GB Mac / Strix: Yes
Strongest model that runs on one 24 GB GPU, Apache-2.0, huge context. Default pick for most local RAG builders.
Details 路 Hugging Face
3DeepSeek V4.1 FlashDeepSeek2026-10-17 (V4.1 Flash 2026-09-10)Causal encoder-decoder MoE with Engram memory, native image input
552B (Yotta Labs; HF safetensors total ~763B incl. extras) total / 8B input / 16B output active
1MMITBF16/native: 510 GB on disk, ~614 GB GPU memory (Yotta Labs)
FP8: no published figure yet
Q8: no published figure yet
Q4: no published figure yet
V4-Flash (older) runs at 2-bit on a 128 GB Mac per LLMCheck
Single Spark (128GB): No (use V4-Flash-0731 at 2-bit)
Dual Spark (256GB): No
Quad Spark (~512GB): Only if quantized, untested unverified
24GB GPU: No
128GB Mac / Strix: No (V4-Flash 2-bit yes)
Top benchmark scores and MIT, but no mainstream local runtime yet and too big for quad Spark natively; V4-Flash-0731 is the practical local DeepSeek.
Details 路 Hugging Face
4MiniMax M3.1 FlashMiniMax2026-10-17 (HF repo; launch reported Oct 19)MoE, native multimodal (text/image/video)
~428B total / 23B active
1Mminimax-community (custom)BF16/native: no published figure yet unverified
FP8: no published figure yet unverified
Q8: no published figure yet unverified
Q4: no published figure yet unverified
Single Spark (128GB): no published figure yet unverified
Dual Spark (256GB): no published figure yet unverified
Quad Spark (~512GB): Likely at 4-bit (unverified) unverified
24GB GPU: No unverified
128GB Mac / Strix: no published figure yet unverified
Brand-new, strong on BenchLeader (62.0), smaller than DeepSeek/Kimi; local tooling still immature.
Details 路 Hugging Face
5Kimi K3Moonshot AI2026-06-13 (HF)MoE (16 of 896 experts), Kimi Delta Attention, native vision
2.8T total / ~104B (Yotta Labs) unverified active
1MKimi K3 License (custom)BF16/native: 1.56 TB MXFP4 (Yotta Labs)
FP8: no published figure yet
Q8: no published figure yet
Q4: 1.56 TB is already ~4-bit
Needs 1.6 TB+ aggregate GPU memory
Single Spark (128GB): No
Dual Spark (256GB): No
Quad Spark (~512GB): No
24GB GPU: No
128GB Mac / Strix: No
Strongest open weights, but not runnable on any home rig, so ranked for awareness, not practicality.
Details 路 Hugging Face
6Qwen3.6-35B-A3BAlibaba Qwen2026-04-15MoE (8 routed + 1 shared)
35B total / 3B active
262,144 native, extensible to ~1.01MApache-2.0BF16/native: no published figure yet
FP8: no published figure yet
Q8: no published figure yet
Q4: no published figure yet
LLMCheck min RAM 24 GB
Single Spark (128GB): Yes
Dual Spark (256GB): Yes
Quad Spark (~512GB): Yes
24GB GPU: Yes
128GB Mac / Strix: Yes
Best speed-per-dollar for laptops/24 GB GPUs; #2 LLMCheck local index.
Details 路 Hugging Face
7Nemotron 3.5 Super VLNVIDIAno published figure yet unverifiedHybrid Mamba-2 + MoE + attention, C-RADIO vision encoder
120B total / 12B active
Up to 1MOpenMDW-1.1BF16/native: no published figure yet
FP8: no published figure yet
Q8: no published figure yet
Q4: no published figure yet
BF16 deploy: 4x H100 or 2x GB200; NVFP4 card targets DGX Spark
Single Spark (128GB): Yes via NVFP4 (NVIDIA card points Spark users to it)
Dual Spark (256GB): Yes
Quad Spark (~512GB): Yes
24GB GPU: No
128GB Mac / Strix: no published figure yet
The most document-focused model here, first-party DGX Spark (NVFP4) support, and a matching embed/rerank stack.
Details 路 Hugging Face
8gpt-oss-120bOpenAI2025-08-04MoE, MXFP4 post-trained
117B total / 5.1B active
no published figure yet unverifiedApache-2.0BF16/native: no published figure yet
FP8: no published figure yet
Q8: no published figure yet
Q4: Fits a single 80 GB GPU in MXFP4 (model card)
Single Spark (128GB): Yes
Dual Spark (256GB): Yes
Quad Spark (~512GB): Yes
24GB GPU: No
128GB Mac / Strix: Yes (fits in 80 GB)
Over a year old and behind the Chinese MoEs on benchmarks, but the most plug-and-play 128 GB model with a clean license.
Details 路 Hugging Face
9Gemma 4 26B-A4BGoogle DeepMindno published figure yet unverifiedMoE (8 of 128 experts + 1 shared), hybrid local/global attention, multimodal
25.2B total / 3.8B active
256KApache-2.0BF16/native: no published figure yet
FP8: no published figure yet
Q8: no published figure yet
Q4: no published figure yet
LLMCheck min RAM 18 GB
Single Spark (128GB): Yes
Dual Spark (256GB): Yes
Quad Spark (~512GB): Yes
24GB GPU: Yes
128GB Mac / Strix: Yes
Fast, Apache-2.0, strong on 24 GB; r/LocalLLaMA favorite for dialogue.
Details 路 Hugging Face
10MiMo-V2.6-FlashXiaomi2026-09-27Sparse MoE (8 of 256 experts)
309B total / 15B active
1MMITBF16/native: no published figure yet
FP8: no published figure yet
Q8: no published figure yet
Q4: no published figure yet
LLMCheck min RAM 170 GB; needs 192 GB+ Mac
Single Spark (128GB): No
Dual Spark (256GB): Yes (inferred from 170 GB min) unverified
Quad Spark (~512GB): Yes
24GB GPU: No
128GB Mac / Strix: No
#1 on LLMCheck local index (Oct 18), MIT, great dual-Spark target.
Details 路 Hugging Face

Spark fit is estimated from published memory sizes, not tested on Spark hardware. Speeds come from the cited sources. Entries marked "hosted, not local" are cloud API speeds, and "ESTIMATE" entries are estimates. Neither is a local measurement.

Best for laptops (under 15B)

ModelParamsContextLicenseMemorySpeedNoteSources
Gemma 4 12B11.95B dense256KApache-2.0~7 GB at 4-bit (LLMCheck)19 tok/s on 32 GB Mac mini M6 (LLMCheck)Text, image and audio inputsource source
Gemma 4 E4B4.5B effective (8B with embeddings)128KApache-2.0no published figure yetno published figure yetTiny and fast; audio inputsource
NVIDIA Nemotron 3.5 Bolt E4Bno published figure yet unverifiedno published figure yet unverifiedno published figure yet unverified4GB variant exists (repo name)no published figure yetPairs with Nemotron-3.5-Embed-1B for an all-NVIDIA laptop stacksource
MiMo-V2.6-Distill-Qwen-9B9B (repo name)no published figure yet unverifiedno published figure yet unverifiedno published figure yetno published figure yetDistilled from MiMo-V2.6source

Laptop speeds are community measurements on the hardware named in each entry.

Honorable mentions

Announced but not released

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