Compare/Qwen3.5 2B (Reasoning) vs LFM2 24B A2B

Qwen3.5 2B (Reasoning)vsLFM2 24B A2B

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

Alibaba

Qwen3.5 2B (Reasoning)

Input
$0.02/M
Output
$0.1/M
Speed
357 tok/s
TTFT
0.54s
Liquid AI

LFM2 24B A2B

Input
$0.03/M
Output
$0.12/M
Speed
203 tok/s
TTFT
0.22s

Winner by Category

Cheaper
Qwen3.5 2B (Reasoning)
Faster (tok/s)
Qwen3.5 2B (Reasoning)
Lower Latency
LFM2 24B A2B
Benchmarks (2-5)
LFM2 24B A2B

Pricing Comparison

MetricQwen3.5 2B (Reasoning)LFM2 24B A2B
Input ($/M tokens)$0.02$0.03
Output ($/M tokens)$0.1$0.12
Cost for 1M input + 100K output tokens:
Qwen3.5 2B (Reasoning)$0.03
LFM2 24B A2B$0.04

Speed Comparison

Output Speed (tokens/s) — higher is better
Qwen3.5 2B (Reasoning)
357 tok/s
LFM2 24B A2B
203 tok/s
Time to First Token (seconds) — lower is better
Qwen3.5 2B (Reasoning)
0.54s
LFM2 24B A2B
0.22s

Benchmark Comparison

Data from Artificial Analysis API — 12 benchmarks

Intelligence Index
16.310.5
Coding Index
3.53.6
Math Index
GPQA Diamond
45.6%47.4%
MMLU-Pro
LiveCodeBench
AIME 2025
MATH-500
Humanity's Last Exam
2.1%4.4%
SciCode
2.8%10.9%
IFBench
31.5%45.9%
TerminalBench
3.8%0.0%
Qwen3.5 2B (Reasoning)2 wins
5 winsLFM2 24B A2B

Frequently Asked Questions

Which is cheaper, Qwen3.5 2B (Reasoning) or LFM2 24B A2B?

Qwen3.5 2B (Reasoning) is cheaper overall. Its blended price (3:1 input/output ratio) is $0.04/M tokens vs $0.05/M for LFM2 24B A2B.

Which model performs better on benchmarks?

LFM2 24B A2B wins 5 out of 12 benchmarks compared to 2 for Qwen3.5 2B (Reasoning). See the detailed benchmark chart above for per-category results.

Which is faster for real-time applications?

Qwen3.5 2B (Reasoning) generates tokens faster at 357 tok/s vs 203 tok/s. However, LFM2 24B A2B has lower time-to-first-token (0.22s vs 0.54s).

When should I use Qwen3.5 2B (Reasoning) vs LFM2 24B A2B?

Choose based on your priorities: Qwen3.5 2B (Reasoning) for lower cost, LFM2 24B A2B for stronger benchmark performance, and Qwen3.5 2B (Reasoning) for faster generation. For latency-sensitive apps, check the TTFT comparison above.