LFM2.5-24B-A2B vs o3 Pro
LFM2.5-24B-A2B costs 114.3x less per output token than o3 Pro ($0.70 vs $80.00 per million). Updated October 21, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- No data
- Output $/M
- $0.70
- Coding
- No data
- Overall
- No data
- Output $/M
- $80.00
LFM2.5-24B-A2B or o3 Pro: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick LFM2.5-24B-A2B for output tokens 114.3x cheaper ($0.70 vs $80.00 per million).
No benchmark has tested both yet. LFM2.5-24B-A2B has none yet; o3 Pro on Aider polyglot, WeirdML and AA Intelligence Index. Compare them on price and context instead.
Which one for your work
Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.
Coding
Vibe Coding Index, six public coding benchmarks
No call
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
No call
Only o3 Pro has a AA Intelligence Index result, 21.9.
Directional only
Long documents
Listed context window
o3 Pro
o3 Pro takes 200K tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
LFM2.5-24B-A2B
LFM2.5-24B-A2B $0.0004, o3 Pro $0.060 per turn.
List prices
At a glance
- Coding index
- LFM2.5-24B-A2B not benchmarked, o3 Pro not benchmarked.
- Widest category
- None yet: no category has been tested on both models.
- Widest single gap
- None yet: no benchmark has tested both models.
- Output price
- LFM2.5-24B-A2B $0.70 against o3 Pro $80.00 per million output tokens, 114.3x apart.
- Context window
- LFM2.5-24B-A2B takes 128K tokens, o3 Pro 200K.
Benchmark by benchmark
Every board either model has a result on, a category to a fold; bars are each result on a 0 to 100 scale. Only one model is measured on each, so no row names a leader.
CodingDirectional onlySix of these boards feed the Vibe Coding Index2 boards measured
| Benchmark | LFM2.5-24B-A2B | o3 Pro | Leader |
|---|---|---|---|
| Aider polyglot | Not measured | 84.9% | Only o3 Pro measured |
| WeirdML | Not measured | 58.2% | Only o3 Pro measured |
| Neither model has a result on the other 37 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | LFM2.5-24B-A2B | o3 Pro | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 21.9 | Only o3 Pro measured |
| Epoch Capabilities Index | Not measured | 147.3 | Only o3 Pro measured |
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index4 boards measured
| Benchmark | LFM2.5-24B-A2B | o3 Pro | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | Not measured | 84.5% | Only o3 Pro measured |
| ARC-AGI | Not measured | 59.3% | Only o3 Pro measured |
| ARC-AGI-2 | Not measured | 4.9% | Only o3 Pro measured |
| Kagi LLM Benchmark | Not measured | 72.1% | Only o3 Pro measured |
| Neither model has a result on the other 18 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index4 boards measured
| Benchmark | LFM2.5-24B-A2B | o3 Pro | Leader |
|---|---|---|---|
| DTBench | Not measured | 86.9% | Only o3 Pro measured |
| LMCA | Not measured | 38.5% | Only o3 Pro measured |
| Fiction.LiveBench | Not measured | 97.2% | Only o3 Pro measured |
| Creative writing (Lech Mazur) | Not measured | 84.4% | Only o3 Pro measured |
| Neither model has a result on the other 42 boards here | |||
What each workload costs
Three fixed token mixes at each model's listed price, so per-token rates become a bill.
Chat turn
1K input + 500 output tokens
LFM2.5-24B-A2B costs less
Repository review
50K input + 3K output tokens
LFM2.5-24B-A2B costs less
Agent loop
200K input + 10K output tokens
LFM2.5-24B-A2B costs less
Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.
Specification differences
The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.
| Specification | LiquidAI LFM2.5-24B-A2B | OpenAI o3 Pro |
|---|---|---|
| Maker | Liquid | OpenAI |
| Weights | Open weights | No public weights listed |
| Released | October 13, 2026 | June 10, 2025 |
| Context window | 128K | 200K |
| Input $/Mtok | $0.05 | $20.00 |
| Output $/Mtok | $0.70 | $80.00 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is LFM2.5-24B-A2B better than o3 Pro for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick LFM2.5-24B-A2B for output tokens 114.3x cheaper ($0.70 vs $80.00 per million).
Which is cheaper, LFM2.5-24B-A2B or o3 Pro?
LFM2.5-24B-A2B costs $0.05 per million input tokens and $0.70 per million output tokens; o3 Pro costs $20.00 and $80.00. Cost per solved task is known for neither of them.
Which has the bigger context window, LFM2.5-24B-A2B or o3 Pro?
o3 Pro, with 200K tokens against 128K.
Has any benchmark tested both LFM2.5-24B-A2B and o3 Pro?
No benchmark has tested both yet. LFM2.5-24B-A2B has none yet; o3 Pro on Aider polyglot, WeirdML and AA Intelligence Index. Compare them on price and context instead. Data as of October 21, 2026.