Best Local LLMs for Offline AI

作者: Jakub Rusinowski · 最后更新: 2026年10月15日

A model that works with no internet connection at all — on a laptop, in the field, or inside an air-gapped network.

Top pick: Ternary Bonsai 27B

Scores 96.9/100 for fully offline and air-gapped use. 27B parameters, needing about 6.6 GB at Ternary (1.58-bit, ~1.71 bpw), 256K context, Apache 2.0.

Ranked for fully offline and air-gapped use

ModelScoreParamsContextLicenceQuality index
1. Ternary Bonsai 27B96.927B256KApache 2.0— (estimated)
2. Ternary Bonsai 2 27B9327B256KApache-2.0— (estimated)
3. Gemma 4 12B (Unified)92.412B125KApache-2.0— (estimated)
4. Qwen 3.7 35B-A3B92.135B256KApache-2.0— (estimated)
5. Qwen 3 14B91.915B125KApache 2.0— (estimated)
6. Qwen 3.6 35B-A3B91.535B256KApache-2.0— (estimated)

Frontier open-weight models (multi-GPU / private cloud)

These also score for fully offline and air-gapped use, but none runs on a single consumer GPU or workstation, so they are listed apart rather than ranked against the local picks above.

Best pick for your memory budget

The strongest model overall is rarely the right answer — what matters is the strongest model that fits the memory you have. These picks are re-ranked per tier, so each one uses its budget rather than simply being small.

MemoryTypical hardwareRecommended models
8 GBRTX 4060, RTX 3070, base MacBook AirTernary Bonsai 27B (96.9)
Ternary Bonsai 2 27B (93)
GLM-6 9B (90.9)
12 GBRTX 3060 12 GB, RTX 5070Ternary Bonsai 27B (96.1)
Gemma 4 12B (Unified) (93.2)
Qwen 3 14B (92.7)
16 GBRTX 5080, RTX 4080, RX 9070 XTTernary Bonsai 27B (94.1)
Qwen 3 14B (92.7)
Mistral Small 3.1 24B (92.4)
24 GBRTX 4090, RTX 3090, RX 7900 XTXQwen 3.7 35B-A3B (95.6)
Gemma 4 31B (95.1)
Qwen 3.6 35B-A3B (94.9)
48 GBRTX 6000 Ada, MacBook Pro M4 Max 48 GBGLM-5.1 72B (95.2)
Qwen 3.5 72B (93.8)
Qwen 3.7 35B-A3B (93.5)
128 GB+Mac Studio, DGX Spark, multi-GPUQwen 3.5 122B-A10B (MoE) (93.7)
GPT-OSS 120B (93.2)
Qwen 3.5 122B-A10B (93)

How this ranking works

The lowest quality floor in the set (40) and the strongest tag weighting toward small, low-memory models. Offline use is constrained by the hardware you happen to have with you, so a model that runs on 8 GB and never stalls beats a stronger model that needs a desktop.

Worked example — Ternary Bonsai 27B: capability 88.6 × 0.389, quality 87.7 × 0.229, context 100 × 0.149, license 70 × 0.062, accessibility 100 × 0.172 + 6 tag bonus (laptop, on-device).

Requirements applied: context floor 8,192 tokens (ideal 65,536), quality floor 40, licence weight 0.6, latency weight 0.7.

Running fully offline and air-gapped use locally

FAQ

What is the best local LLM for fully offline and air-gapped use?

Ternary Bonsai 27B, scoring 96.9/100 against this workload's published requirements. 159 models qualified.

What hardware do I need for fully offline and air-gapped use?

A credible answer starts at 8 GB of memory. Larger budgets unlock materially stronger models — the table above lists the best pick at each tier.

How were these models ranked?

The lowest quality floor in the set (40) and the strongest tag weighting toward small, low-memory models. Offline use is constrained by the hardware you happen to have with you, so a model that runs on 8 GB and never stalls beats a stronger model that needs a desktop.

Hardware for This Workload

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