Qwen3.8 2.4T A95B
Qwenothertext

Qwen3.8 2.4T A95B

Updated Aug 17, 2026
Parameters
2446.2B
Context
262,144
License
other
Updated
Aug 17, 2026

Intelligence benchmarks

Artificial Analysis indexes - compared with the best open and proprietary models

Intelligence

57.7

AA Index

Agentic

57.1

AA Index

Intelligence Index - Qwen3.8 2.4T A95B vs. the field

Best open-weight models (you can run locally) and leading proprietary models for context.

Claude Opus 5 (max)
63.1
closed
Claude Fable 5 (with fallback)
62.1
closed
GPT-5.6 Sol (max)
60.9
closed
Grok 4.6 (high)
60.9
closed
Kimi K3
59.7
open
Qwen3.8 Max
58.1
closed
Qwen3.8 2.4T A95B
57.7
open

Agentic Index comparison

Claude Opus 5 (max)
59.2
closed
Grok 4.6 (high)
58.7
closed
Qwen3.8 Max
58.4
closed
GPT-5.6 Sol (max)
57.8
closed
Qwen3.8 2.4T A95B
57.1
open
Claude Fable 5 (with fallback)
56.6
closed
Kimi K3
54.3
open

Benchmark data from Artificial Analysis · updated 2026-08-17.

Standard benchmarks

Performance across standard evaluations

BenchmarkScore
GPQA93.5

Will it run on your hardware?

Pick your GPU memory - see which quantizations fit, and the cheapest card for the rest

Too big for 24 GB at any quant
0 of 4 quantizations fit Qwen3.8 2.4T A95B with real runtime overhead.
Q4_K_M
1419 GB
Q5_K_M
1737 GB
Q8_0
2617 GB
FP16
4892 GB
fits tight too big

Need an exact figure for your context length? Use the VRAM calculator.

Run it locally

Copy-paste - running in under a minute

vLLMOpenAI-compatible API
vllm serve Qwen/Qwen3.8-2.4T-A95B-FP8

New to this? Start with Ollama · serve to many users with vLLM.

Deep dive

Notes, sources, and the full write-up

Qwen3.8 2.4T A95B is a 2446.2B-parameter other model from Alibaba. It scores 57.7 on the Artificial Analysis Intelligence Index. At Q4_K_M it needs roughly 1419 GB of VRAM, placing it in the 48 GB+ / multi-GPU hardware tier.

Benchmarks

Artificial Analysis Intelligence Index - Qwen3.8 2.4T A95B vs. leading closed models:

ModelIntelligenceCodingGPQA
Qwen3.8 2.4T A95B57.7-93.5
Claude Opus 5 (max)63.1-93.2
Claude Fable 5 (with fallback)62.1-92.6
GPT-5.6 Sol (max)60.9-94.1
Grok 4.6 (high)60.9-94.9
Qwen3.8 Max58.1-92.7

Source: Artificial Analysis (2026-08-15).

Popularity

Qwen3.8 2.4T A95B has 9,334 downloads in the last month on HuggingFace and 184 likes.

Frequently asked

Quick answers to common questions

How much VRAM does Qwen3.8 2.4T A95B need?

Qwen3.8 2.4T A95B with 2446.2B parameters needs approximately 1419 GB at Q4_K_M quantization. Use our VRAM calculator for an exact estimate.

Is Qwen3.8 2.4T A95B better than other Qwen models?

Qwen3.8 2.4T A95B has 2446.2B parameters with 262,144 context - a strong choice for general use.

What license is Qwen3.8 2.4T A95B under?

Qwen3.8 2.4T A95B is released under the other license, making it suitable for most commercial and personal projects.

What hardware runs Qwen3.8 2.4T A95B well?

With 2446.2B parameters, Qwen3.8 2.4T A95B requires adequate VRAM. High-end GPUs like the RTX 4090 (24GB), RTX 5090 (32GB), or Mac Studio with unified memory are good options. Check our hardware directory for specific recommendations.

What is the best quantization for Qwen3.8 2.4T A95B?

Q4_K_M is the recommended sweet spot - ~98% of FP16 quality at ~27% of the size. Q5_K_M (~1737 GB) is an option if you have spare VRAM. Use our VRAM calculator to compare.

How long can Qwen3.8 2.4T A95B's context window handle?

Qwen3.8 2.4T A95B supports a 262,144-token context window - enough for very long documents, codebases, or multi-turn conversations. Real-world usable context may vary by implementation.

What models compete with Qwen3.8 2.4T A95B?

Qwen3.8 2.4T A95B competes with other 1223B–3669B. Browse our model directory for comparisons, benchmarks, and community reviews to find the best fit.

Nearby options

Similar models and compatible hardware by spec

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