← All guides
Hardware June 23, 2026

Best Local LLM for 96GB RAM (2026): gpt-oss 120B at Q5

96GB is a strong position in June 2026. Three new models arrived that fit comfortably: Llama 4 Scout (10M context, ~58GB at Q4), DeepSeek V4 Flash (~80GB at Q4, top coding), and more headroom for gpt-oss 120B at premium Q5 quality. The Mac Studio M5 Ultra 96GB (1.2 TB/s bandwidth) replaced the M3 Ultra 96GB on 25 August 2026.

Apple Mac for 96GB RAM local AI on Amazon
🛒 BEST MAC FOR 96GB RAM Apple MacBook Pro · 48GB+ unified memory 96GB runs 100B-class MoE models at premium quants — a Mac Studio private team AI server. Check current price on Amazon →
🎮 PREFER A DISCRETE GPU? 96 GB ON ONE CARD

Rather have a GPU than unified memory? The RTX PRO 6000 Blackwell packs 96 GB of VRAM — the same memory budget as a 96 GB Mac, for 100B-class MoE and 70B at long context without CPU offload.

Updated June 2026 — new models at 96GB
  • Llama 4 Scout — 109B/17B MoE, ~58GB at Q4, 10M context window, fits with lots of headroom
  • DeepSeek V4 Flash — 284B/13B MoE, ~80GB at Q4, top SWE-Bench coding, via ds4 engine
  • Llama 4 Maverick (400B) does NOT fit 96GB — needs 128GB minimum at Q4

Bottom Line (2026)

  • Best overall pick: gpt-oss 120B at Q5_K_M (cleanest tool calls, production-proven)
  • Best long documents: Llama 4 Scout at Q4 — 10M context, ~58GB, fits with 38GB headroom
  • Best coding: DeepSeek V4 Flash at Q4 — ~80GB, top SWE-Bench, via ds4 engine
  • Best fast inference: Qwen 3.6 35B-A3B at Q8_0 (paired as fast second model)
  • Best premium reasoning: Mistral Small 4 (119B-A6B) at Q5_K_M

New, August 25 2026: Apple brought the 256GB Mac Studio back with the M5 Ultra — 1.2 TB/s bandwidth, ships September 22. If this tier is not enough memory, that is now the machine to look at.

## Top Picks for 96GB RAM

1. Qwen 3.5 122B-A10B (Q4_K_M) — best general-purpose

The Qwen 3.5 medium series flagship MoE released February 24, 2026. 122B total parameters, 10B active per token = 14B-class inference speed with 122B-class knowledge. About 75GB at Q4_K_M.

ollama pull qwen3.5:122b
openclaw config set agents.defaults.models.chat ollama/qwen3.5:122b

Speed: ~18-25 tok/sec on M3 Max 96GB. Note: Qwen 3.5 has the Ollama tool-calling bug (issue #14493) that can affect strict OpenClaw autonomous loops. Pair with gpt-oss 120B for the agent path.

2. gpt-oss 120B (Q5_K_M) — best for OpenClaw production

OpenAI’s flagship at Q5 uses about 80GB. The cleanest tool-call JSON of any open-weight model. The “ship it for OpenClaw” pick when reliability matters more than benchmark scores.

ollama pull gpt-oss:120b-q5_K_M
openclaw config set agents.defaults.models.chat ollama/gpt-oss:120b-q5_K_M
openclaw run --agent --max-hours 12 "Continuous CI agent"

3. Mistral Small 4 (119B-A6B MoE) at Q5_K_M — premium reasoning

Mistral’s March 16, 2026 release at Q5 uses about 80GB. 6B active parameters per token gives faster inference than gpt-oss 120B Q5 with comparable reasoning depth. Replaces the older Mistral Large 123B from 2024.

ollama pull mistral-small-4:q5_K_M

4. Quad-Model Setup at 96GB

Keep four specialized models loaded:

# Chat (Qwen 3.6 27B Q8) — 33GB
# Agent loops (gpt-oss 20B Q8) — 22GB
# Code (Nemotron Cascade 2 30B Q5) — 22GB
# Utility (Qwen 3.5 4B Q8) — 5GB

openclaw config set agents.defaults.models.chat ollama/qwen3.6:27b-q8_0
openclaw config set agents.defaults.models.agent ollama/gpt-oss:20b-q8_0
openclaw config set agents.defaults.models.code ollama/nemotron-cascade-2:30b-q5_K_M
openclaw config set agents.defaults.models.utility ollama/qwen3.5:4b-q8_0
openclaw config set agents.defaults.keep_alive 2h

openclaw models status

Total: ~82GB models + context + OS = comfortable on 96GB.

5. Llama 3.3 70B (Q6_K) — still works

The old standard at Q6_K uses about 60GB. Still solid but Qwen 3.5 122B-A10B and gpt-oss 120B both match or exceed it on most April 2026 benchmarks.

What Fits in 96GB

ModelQuantRAM UsedTool Calling
Qwen 3.5 122B-A10BQ4_K_M~78 GBFair (Ollama bug)
gpt-oss 120BQ5_K_M~82 GBExcellent (production)
Mistral Small 4 119B-A6BQ5_K_M~82 GBGood
Llama 3.3 70BQ6_K~62 GBExcellent
Quad-model setupmixed~82 GBExcellent
Qwen 3.6 27B + Qwen 3.6 35B-A3B (dual)Q8 + Q6~63 GBExcellent

Common Mistakes at 96GB

  1. Picking Qwen 3.5 122B-A10B for OpenClaw without gpt-oss fallback. The Ollama tool-calling bug (issue #14493) affects all Qwen 3.5 variants. Always pair with gpt-oss 120B for the agent path.
  2. Loading three models without setting keep_alive. Ollama unloads idle models in 5 minutes by default. Set keep_alive 2h so model swaps don’t pause your workflow.
  3. Running 235B+ models at IQ2 because “more parameters.” Quality at IQ2 is so degraded that a 122B-A10B at Q4 beats it. Skip the squeeze.
  4. Skipping the new Qwen 3.6 35B-A3B because the 122B-A10B fits. The 35B-A3B is faster and excellent for parallel use cases. Keep both for routing.

🛒 Recommended hardware for local AI

The two Macs that handle the workloads on this page.

Amazon affiliate links — we earn a small commission at no cost to you.

Update, 30 October 2026: Apple discontinued the M3 Ultra and M4 Max Mac Studio on 25 August 2026. The new Mac Studio uses the M5 Max (36GB to 128GB) or the M5 Ultra (96GB to 512GB). The M3 Ultra and M4 Max figures on this page still apply to used and clearance units. For the new lineup, see Best Local LLM for Mac Studio.

Hardware That Actually Hits 96GB

  • Mac Studio M2 Max / M3 Max (96GB) — best dedicated host
  • M3 Max / M4 Max MacBook Pro (96GB) — laptop option
  • 2x RTX A6000 48GB = 96GB VRAM (Linux)
  • 4x RTX 3090 24GB = 96GB VRAM (server build)

Before you order parts, check the tested hardware list for current prices by tier.

See Also

Read next

Best Local LLM for 64GB RAM (2026): Qwen3.8 27B at Q8
Best local LLM for 64GB RAM: Qwen3.8 27B at Q8_0 (27.05 GiB). A 64GB Mac gives the GPU 51.84 GiB, so gpt-oss 120B (59.03 GiB) and Llama 4 Scout Q4 do not fit by default. Also Qwen3.6 35B-A3B Q8_0, Gemma 4 31B, Laguna XS 2.1.
Best LLM for 128GB RAM (2026): Local Picks, Llama 4 Maverick
Best local LLMs for 128GB RAM in 2026. Llama 4 Maverick (400B MoE, ~95GB Q4), gpt-oss 120B at Q6, Laguna XS 2.1 (agentic coding, Q8 + huge context), Llama 4 Scout (10M context), DeepSeek V4 Flash via Ollama cloud. Mac Studio M4 Max territory.
Best Local LLM for Mac Studio M3 Ultra (2026): Used Only, 96GB to 512GB
The best local LLM for the Mac Studio M3 Ultra at ~800 GB/s. Apple discontinued the M3 Ultra on August 25, 2026, so every unit is now used. Run 70B at Q8 and 100B+ MoE locally at 96GB, 256GB or 512GB.
Best Local LLM for 48GB VRAM or RAM (2026): Qwen 3.6 27B Q8
Best local LLMs for 48GB RAM in 2026. Qwen 3.6 27B at Q8 (near-FP16), Laguna XS 2.1 (agentic coding, ~36GB Q8), Qwen 3.6 35B-A3B MoE, gpt-oss 20B Q8, Gemma 4 26B-A4B (~15GB). M3 Max 48GB territory.