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URL: https://willitrunai.com/can-run/llama-3.1-70b-on-instinct-mi250-128gb

⇱ Llama 3.1 70B on AMD Instinct MI250 128GB? YES

Can Llama 3.1 70B run on AMD Instinct MI250 128GB?

YES — Runs Great

A82Great
○Estimated from fit model

Llama 3.1 70B needs ~61.3 GB VRAM. AMD Instinct MI250 128GB has 128.0 GB. With Q4_K_M quantization, expect ~55 tok/s.

Runtime: llama.cppCapacity: RoomyBandwidth: HighStack: StandardBottleneck: Balanced
Share:

Operating mode

Choose the run profile you care about

Interactive favors responsiveness, while light API and scale-out lean harder on serving readiness. The fit stays the same, but the recommendation lens changes.

Current mode

Balanced

Balanced for general local use. Keeps the ranking neutral across personal and serving workflows.

Capabilities:

Select quantization to explore

Q4_K_M (Medium quality) — 61.3 GB, 55.4 tok/s, Runs well
61.3 GB required128.0 GB available
48% VRAM used

Fit status

Runs well

Decode

55.4 tok/s

TTFT

3493 ms

Safe context

128K

Memory

61.3 GB / 128.0 GB

Memory breakdown

Weights42.7 GB
KV Cache4.9 GB
Runtime0.9 GB
Headroom12.8 GB

See how fast it feels

See how fast it feelsLlama 3.1 70B on AMD Instinct MI250 128GB
1st promptCold start — includes initialization
>Solve: If a train travels at 60 mph for 2.5 hours, how far does it go?
Let me work through this step by step. Given information: - Speed = 60 mph (miles per hour) - Time = 2.5 hours Formula: Distance = Speed x Time Calculation: Distance = 60 mph x 2.5 h = 150 miles The train travels 150 miles. Double-check: at 60 mph the train covers 60 miles each hour. In half an hour it covers 30 miles. So in 2.5 hours: 60 + 60 + 30 = 150 miles. Confirmed.
2nd promptWarm — model ready, no init overhead
>What if the train stops for 20 minutes halfway?
The stop doesn't change the total distance covered while moving, but it affects total trip time. Breakdown: - First half: 1.25 hours at 60 mph = 75 miles - Stop: 20 minutes (no distance) - Second half: 1.25 hours at 60 mph = 75 miles Total distance: 150 miles (same) Total time: 2.5 h + 0.33 h = 2.83 hours Average speed: 150 / 2.83 = 53 mph The distance stays the same but average speed drops to 53 mph because of the stop.
Estimated: 55.4 tok/s decode · 3.5s TTFT (warm) · 139 tok/s prefill

What limits this setup

This setup is broadly balanced for this model.

No major red flags

This recommendation has enough memory headroom and acceptable estimated speed for the selected workload.

Best improvement path

Performance by workload

WorkloadGradeFitDecodeTTFTContext
ChatARuns well55.4 tok/s1905 ms128K
CodingARuns well55.4 tok/s3493 ms128K
Agentic CodingARuns well55.4 tok/s5081 ms128K
ReasoningARuns well55.4 tok/s4129 ms128K
RAGARuns well55.4 tok/s6352 ms128K

Quantization options

How Llama 3.1 70B (70B params) fits at each quantization level on AMD Instinct MI250 128GB (128.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
27.3 GB
LowA72
Q3_K_S
3
34.3 GB
LowA73
NVFP4
4
39.2 GB
MediumA74
Q4_K_M
4
42.7 GB
MediumA74
Q5_K_M
5
50.4 GB
HighA75
Q6_K
6
57.4 GB
HighA77
Q8_0Best for your GPU
8
74.9 GB
Very HighA79
F16
16
143.5 GB
MaximumF0

Get started

Copy-paste commands to run Llama 3.1 70B on your machine.

Run

ollama run llama3.1

Your hardware

More models your AMD Instinct MI250 128GB can run

ModelParamsGradeDecodeCapabilities
👁 Mistral
Devstral 2 123B Instruct		123BS31.5 tok/s
👁 Alibaba
Qwen 3.5 122B A10B		122BS87.5 tok/s
👁 Mistral
Mistral Small 4 119B		119BS94.8 tok/s
👁 OpenAI
GPT-OSS 120B		117BS33.2 tok/s
👁 Cohere
Command A 111B		111BS35.1 tok/s

Frequently asked questions

See all results for AMD Instinct MI250 128GBSee all hardware for Llama 3.1 70B