Lfm 2.5 1.2 B Thinking vs Qwen 2 1.5 B Instruct: cost comparison
Prices updated 2026-10-30 · computed from live provider data
Short answer: Qwen 2 1.5 B Instruct is cheaper on a
3:1 input/output blend — $0.020 per million tokens versus
$0.028, a 27% difference.
Both offer the same 32,768-token context window, so cost is the deciding factor.
Head to head
| Lfm 2.5 1.2 B Thinking | Qwen 2 1.5 B Instruct | |
|---|---|---|
| Input, per 1M tokens | $0.020 | $0.020 |
| Output, per 1M tokens | $0.050 | $0.020 |
| Blended 3:1, per 1M | $0.028 | $0.020 |
| Context window | 32,768 | 32,768 |
| Vendor | zerogpu | together_ai |
Monthly cost at real volumes
| Workload (input / output) | Lfm 2.5 1.2 B Thinking | Qwen 2 1.5 B Instruct |
|---|---|---|
| 1M in / 250K out | $0.033 | $0.025 |
| 10M in / 2.5M out | $0.325 | $0.250 |
| 100M in / 25M out | $3.25 | $2.50 |
Which should you pick?
Because the context windows are identical, the cheaper option is the better default. Choose Qwen 2 1.5 B Instruct unless you are already standardised on zerogpu tooling and want to avoid a second integration.