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SAVRN Model Hub · Comparisons

Llama-3.3-70B-Instruct vs Qwen-72B

Llama-3.3-70B-Instruct has 70.6B parameters and Qwen-72B has 72.3B parameters; Llama-3.3-70B-Instruct is released under llama3.3 and Qwen-72B under other; at 16-bit, Llama-3.3-70B-Instruct needs about 169.3 GB (1x MI300X from $1.85 an hour) and Qwen-72B about 173.5 GB (1x MI300X from $1.85 an hour).

Published metadata for 2 models, each read from its own repository.
Field Llama-3.3-70B-Instruct
meta-llama/Llama-3.3-70B-Instruct
Qwen-72B
Qwen/Qwen-72B
Publisher Meta Llama Qwen
Task Text generation Text generation
Modality Text Text
Parameters, as reported 70.6B parameters 72.3B parameters
Architecture LlamaForCausalLM QWenLMHeadModel
Library transformers transformers
Context length Not stated 32,768 tokens
Repository size 282.3 GB 144.6 GB
Artifact formats safetensors, pytorch safetensors
License llama3.3 other
Access Access requested at publisher Open weights, no gate
Memory at 16-bit (weights and margin) 169.3 GB 173.5 GB
Cheapest GPUs at 16-bit, per hour 1x MI300X, $1.85 1x MI300X, $1.85
Memory at 4-bit (weights and margin) 42.3 GB 43.4 GB
Cheapest GPUs at 4-bit, per hour 1x MI300X, $1.85 1x MI300X, $1.85
Revision viewed 6f6073b42301 b8e18ac61df6
Downloads reported by the hub 924.1k 4M
Last observed 2026-09-18 2026-09-18

An evaluation row appears only where at least two of these models report the same benchmark with the same stated configuration, metric, unit and setup. Different evaluators stay named in each cell. Values are shown as reported: no unit conversion, no ranking.

Other Reported Results

These results are listed for each model on its own, because the conditions needed to compare them are not stated or do not match. Two results that leave a condition blank are not assumed to share it.

Llama-3.3-70B-Instruct

BenchmarkConditionsResultReported byRevisionDate
Idavidrein/gpqa Task diamondMetric diamondSetup GPQA DiamondComparison conditions not established 51.5152 EvalEval
Reported by a third party
Evaluated revision not stated 2026-04-16
LEXam-Benchmark/LEXam Task mcq_4_choicesMetric mcq_4_choicesComparison conditions not established 28.19 LEXam Leaderboard
Reported by a third party
Evaluated revision not stated 2026-06-02
LEXam-Benchmark/LEXam Task open_questionMetric open_questionComparison conditions not established 41.27 LEXam Leaderboard
Reported by a third party
Evaluated revision not stated 2026-06-02
TIGER-Lab/MMLU-Pro Task mmlu_proMetric mmlu_proComparison conditions not established 65.92 EvalEval
Reported by a third party
Evaluated revision not stated 2026-06-30
joelniklaus/LEXam-hard Task lexam_hardMetric lexam_hardSetup lighteval, LEXam paper prompts, one response per question, no tools; DeepSeek-R1-0528 judge; mean of the German and English means over the 518 questions, 0-100Comparison conditions not established 26.78 SwissLegalEvals per-sample details (lighteval)
Reported by a third party
Evaluated revision not stated 2026-07-12
openai/gsm8k Task gsm8kMetric gsm8kComparison conditions not established 94.8446 EvalEval
Reported by a third party
Evaluated revision not stated 2025-03-19
thamilvendhan/signalbench Task access_denyMetric access_denySetup family=access_deny; n=12Comparison conditions not established 0.0833 thamilvendhan
Reported by a third party
Evaluated revision not stated 2026-07-08
thamilvendhan/signalbench Task memory_labelMetric memory_labelSetup family=memory_label; n=12Comparison conditions not established 0.5833 thamilvendhan
Reported by a third party
Evaluated revision not stated 2026-07-08
thamilvendhan/signalbench Task srcMetric srcSetup SRC overall; deterministic action-based grader, no LLM judge; seed 0, n=75Comparison conditions not established 0.4167 signalbench raw per-item responses
Reported by a third party
Evaluated revision not stated 2026-07-08
thamilvendhan/signalbench Task timeMetric timeSetup family=time; n=12Comparison conditions not established 0.75 thamilvendhan
Reported by a third party
Evaluated revision not stated 2026-07-08

SAVRN's Notes on Llama-3.3-70B-Instruct

At 16-bit the weights alone are 141.1 GB and the working set is 169.3 GB, which puts this 70.6 billion parameter model on one MI300X with 192 GB at $1.85 an hour on-demand. Drop to 8-bit and the need falls to 84.7 GB; 4-bit needs 42.3 GB on the same card. Meta Llama tuned it for multilingual dialogue, text in and text out. Budget 282 GB of disk for the 53 files.

The license is the publisher's own llama3.3 terms and access is gated, so a deployment starts with an approval step and a read of that document. The page lists no context length, so confirm it against the base it derives from, Llama-3.1-70B, before sizing the KV cache. As a rent comparison, the Index shows it served from $0.13 in and $0.40 out per million tokens at Nebius Token Factory up to $1.04 each way at Together AI.

Questions

Which is larger, Llama-3.3-70B-Instruct or Qwen-72B?

Qwen-72B (72.3B parameters) is larger than Llama-3.3-70B-Instruct (70.6B parameters), by the parameter counts their publishers report.

Which is cheaper to run, Llama-3.3-70B-Instruct or Qwen-72B?

At 4-bit, Llama-3.3-70B-Instruct fits on 1x MI300X from $1.85 an hour and Qwen-72B on 1x MI300X from $1.85 an hour, at the lowest on-demand prices the SAVRN Index lists.

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