Compare/Llama 3.2 Instruct 1B vs Qwen3.5 0.8B (Reasoning)

Llama 3.2 Instruct 1BvsQwen3.5 0.8B (Reasoning)

Side-by-side comparison of pricing, 12 benchmarks, and generation speed.

Meta

Llama 3.2 Instruct 1B

Input
$0.05/M
Output
$0.05/M
Speed
92 tok/s
TTFT
0.60s
Alibaba

Qwen3.5 0.8B (Reasoning)

Input
$0.01/M
Output
$0.05/M
Speed
TTFT

Winner by Category

Cheaper
Qwen3.5 0.8B (Reasoning)
Faster (tok/s)
Llama 3.2 Instruct 1B
Lower Latency
Qwen3.5 0.8B (Reasoning)
Benchmarks (10-1)
Llama 3.2 Instruct 1B

Pricing Comparison

MetricLlama 3.2 Instruct 1BQwen3.5 0.8B (Reasoning)
Input ($/M tokens)$0.05$0.01
Output ($/M tokens)$0.05$0.05
Cost for 1M input + 100K output tokens:
Llama 3.2 Instruct 1B$0.06
Qwen3.5 0.8B (Reasoning)$0.02

Speed Comparison

Output Speed (tokens/s) — higher is better
Llama 3.2 Instruct 1B
92 tok/s
Qwen3.5 0.8B (Reasoning)
Time to First Token (seconds) — lower is better
Llama 3.2 Instruct 1B
0.60s
Qwen3.5 0.8B (Reasoning)

Benchmark Comparison

Data from Artificial Analysis API — 12 benchmarks

Intelligence Index
6.310.5
Coding Index
0.60.0
Math Index
0.0
GPQA Diamond
19.6%11.1%
MMLU-Pro
20.0%
LiveCodeBench
1.9%
AIME 2025
0.0%
MATH-500
14.0%
Humanity's Last Exam
5.3%1.2%
SciCode
1.7%0.0%
IFBench
22.8%21.5%
TerminalBench
0.0%0.0%
Llama 3.2 Instruct 1B10 wins
1 winsQwen3.5 0.8B (Reasoning)

Frequently Asked Questions

Which is cheaper, Llama 3.2 Instruct 1B or Qwen3.5 0.8B (Reasoning)?

Qwen3.5 0.8B (Reasoning) is cheaper overall. Its blended price (3:1 input/output ratio) is $0.02/M tokens vs $0.05/M for Llama 3.2 Instruct 1B.

Which model performs better on benchmarks?

Llama 3.2 Instruct 1B wins 10 out of 12 benchmarks compared to 1 for Qwen3.5 0.8B (Reasoning). See the detailed benchmark chart above for per-category results.

Which is faster for real-time applications?

Llama 3.2 Instruct 1B generates tokens faster at 92 tok/s vs 0 tok/s. However, Qwen3.5 0.8B (Reasoning) has lower time-to-first-token (0.00s vs 0.60s).

When should I use Llama 3.2 Instruct 1B vs Qwen3.5 0.8B (Reasoning)?

Choose based on your priorities: Qwen3.5 0.8B (Reasoning) for lower cost, Llama 3.2 Instruct 1B for stronger benchmark performance, and Llama 3.2 Instruct 1B for faster generation. For latency-sensitive apps, check the TTFT comparison above.