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VECTOR WIREAI INTELLIGENCE
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Llama 3.2 Instruct 1B vs Qwen3 1.7B (instruct)

Meta · released

Wins 1 of 2 areas

Following instructions

Alibaba

Wins 1 of 2 areas

Reasoning

The two are evenly matched.Llama 3.2 Instruct 1B is better at following instructions; Qwen3 1.7B (instruct) at reasoning.

Scores updated · 16 tests both models report · How we compare

Where each one wins

Tests won in each of the two areas where both have results. Each piece is one test, so a longer bar means more evidence; grey means the two scored within a point of each other.

Reasoning and following instructions rest on a single test each.

What it costs

Prices per million tokens, roughly 750,000 words. The bars show the cost of a million tokens read plus a million written.

Llama 3.2 Instruct 1B$0.03 to read · $0.20 to write$0.23Price from meta-llama
Qwen3 1.7B (instruct)No current price is tracked.

The biggest differences

The tests each model wins by the widest margin, up to three each. Scores are out of 100.

Where Llama 3.2 Instruct 1B pulls ahead

  • Follows unfamiliar, precisely checkable instructionsIFBench+1.5points aheadLlama 3.2 Instruct 1B22.8Qwen3 1.7B (instruct)21.3

Where Qwen3 1.7B (instruct) pulls ahead

  • Graduate-level biology, physics and chemistry questionsGPQA Diamond+15.3points aheadQwen3 1.7B (instruct)34.9Llama 3.2 Instruct 1B19.6

Every test, side by side

All 16 tests both models report. The winning score is in its model's colour; marks a score checked independently.

ReasoningQwen3 1.7B (instruct)

Full reasoning ranking

Following instructionsLlama 3.2 Instruct 1B
  • IFBenchLlama 3.2 Instruct 1B by 1.522.821.3+1.5

Full following instructions ranking

Other results14 tests, not counted

Tests outside the eight areas. They are not counted above: several are summary scores built from other tests, or the same test under another name.

  • MATH-500 (EM)Qwen3 1.7B (instruct) by 4723.470.4+47
  • J-MATH500Qwen3 1.7B (instruct) by 4511.456.4+45
  • Avg.Qwen3 1.7B (instruct) by 32.918.351.2+32.9
  • J-BFCLv3Qwen3 1.7B (instruct) by 31.421.152.5+31.4
  • JHumanEval+Qwen3 1.7B (instruct) by 29.917.747.6+29.9
  • BFCL v3Qwen3 1.7B (instruct) by 24.921.446.3+24.9
  • Domain AvgQwen3 1.7B (instruct) by 23.621.244.8+23.6
  • MMLU-ProQwen3 1.7B (instruct) by 22.120.842.9+22.1
  • IFEvalQwen3 1.7B (instruct) by 21.352.473.7+21.3
  • J-GSM8KQwen3 1.7B (instruct) by 20.825.246+20.8
  • JMMLU-ProXQwen3 1.7B (instruct) by 14.915.930.8+14.9
  • JMMLUQwen3 1.7B (instruct) by 13.73447.7+13.7
  • JGPQALlama 3.2 Instruct 1B by 632.326.3+6
  • GSM8KLlama 3.2 Instruct 1B by 235.733.7+2

Questions people ask

Which is better, Llama 3.2 Instruct 1B or Qwen3 1.7B (instruct)?

Llama 3.2 Instruct 1B and Qwen3 1.7B (instruct) each win one of the two areas where both have results. Llama 3.2 Instruct 1B wins following instructions; Qwen3 1.7B (instruct) wins reasoning.

How do you compare the two?

We use the 16 benchmark tests both models have published scores on. The verdict counts the 2 tests in the eight capability areas, and a gap under one point (ten on rating-style scales) counts as a tie. The other 14 are listed but not counted, because several are summary scores or repeat a test. Each score is the one shown on the model's own page.