>>8 recommended models

Best Local AI Models for Long Context

Long context models can process entire documents, codebases, and extended conversations in a single prompt. While most models default to 4K-8K context, several open-weight models support 32K to 128K+ tokens locally. More context means more RAM usage, so hardware matters even more for these workloads.

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Get long context model recommendations tailored to your specific hardware.

MacBook Air

16GB RAM

Long Context models for MacBook Air →

MacBook Pro

32GB RAM

Long Context models for MacBook Pro →

Mac Mini

16GB RAM

Long Context models for Mac Mini →

Mac Studio

64GB RAM

Long Context models for Mac Studio →

iPhone 16 Pro

8GB RAM

Long Context models for iPhone 16 Pro →

Top Long Context Models (All Hardware)

#ModelSizeRAMBest ForQualityOllama
01Qwen3.6 27B27B24 GBCoding, Quality, Long context
94
02Qwen3 235B A22B235B192 GBQuality, Reasoning
98
03Llama 3.3 70B Instruct70B48 GBQuality, Coding
98
04Llama 4 Scout109B80 GBLong context, Quality, Multimodal
93
05Llama 3.1 70B Instruct70B48 GBQuality, Coding
99
06Llama 3.1 405B Instruct405B256 GBQuality, Reasoning, Coding
99
07Llama 4 Maverick400B256 GBFrontier quality, Long context
97
08Gemma 4 31B31B32 GBQuality, Coding, Multimodal
92

RAM Requirements

Qwen3.6 27B
18 GB
min 24 GB
Qwen3 235B A22B
130 GB
min 192 GB
Llama 3.3 70B Instruct
42 GB
min 48 GB
Llama 4 Scout
67 GB
min 80 GB
Llama 3.1 70B Instruct
42 GB
min 48 GB
Llama 3.1 405B Instruct
243 GB
min 256 GB
Llama 4 Maverick
245 GB
min 256 GB
Gemma 4 31B
20 GB
min 32 GB

Frequently Asked Questions

What is the best local model for long documents?+
Qwen2.5 7B supports 32K context natively and performs well on document analysis. For 128K context, larger models like Qwen2.5 14B or Llama 3.1 8B (which supports 128K) are better choices if you have 24GB+ RAM.
How much RAM does a long context model need?+
Context length directly impacts RAM usage. A 7B model at 4K context uses about 5.5GB, but at 32K context it may use 8-10GB. At 128K context, even a 7B model can need 16GB+ RAM. Plan for roughly 2x the base RAM requirement at maximum context.
Can I analyze a full codebase locally?+
Yes, with limitations. A 128K context window holds roughly 90K words or 300-400 files of typical code. For larger codebases, you will need to chunk the input or use tools that intelligently select relevant files.
Does long context slow down the model?+
Yes. Longer prompts increase time-to-first-token because the model must process more input. At 32K tokens, expect 3-8 seconds to start generating. At 128K tokens, it can take 15-30+ seconds depending on hardware.

Other Use Cases

CodingChatReasoningTranslationCreative WritingPrivacy

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