GPT-5.4 Pro vs LFM2.5-24B-A2B
LFM2.5-24B-A2B costs 257.1x less per output token than GPT-5.4 Pro ($0.70 vs $180.00 per million). Updated October 22, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- No data
- Output $/M
- $180.00
- Coding
- No data
- Overall
- No data
- Output $/M
- $0.70
GPT-5.4 Pro or LFM2.5-24B-A2B: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick GPT-5.4 Pro for a larger context window (1.05M against 128K tokens).
No benchmark has tested both yet. GPT-5.4 Pro has results on WeirdML, Epoch Capabilities Index and GPQA Diamond (Epoch AI run); LFM2.5-24B-A2B has none yet. 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
Long documents
Listed context window
GPT-5.4 Pro
GPT-5.4 Pro takes 1.05M tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
LFM2.5-24B-A2B
GPT-5.4 Pro $0.120, LFM2.5-24B-A2B $0.0004 per turn.
List prices
At a glance
- Coding index
- GPT-5.4 Pro not benchmarked, LFM2.5-24B-A2B 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
- GPT-5.4 Pro $180.00 against LFM2.5-24B-A2B $0.70 per million output tokens, 257.1x apart.
- Context window
- GPT-5.4 Pro takes 1.05M tokens, LFM2.5-24B-A2B 128K.
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 Index1 board measured
| Benchmark | GPT-5.4 Pro | LFM2.5-24B-A2B | Leader |
|---|---|---|---|
| WeirdML | 57.4% | Not measured | Only GPT-5.4 Pro measured |
| Neither model has a result on the other 38 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | GPT-5.4 Pro | LFM2.5-24B-A2B | Leader |
|---|---|---|---|
| Epoch Capabilities Index | 159.6 | Not measured | Only GPT-5.4 Pro measured |
| Neither model has a result on the other 1 board here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index5 boards measured
| Benchmark | GPT-5.4 Pro | LFM2.5-24B-A2B | Leader |
|---|---|---|---|
| GPQA Diamond (Epoch AI run) | 94.6% | Not measured | Only GPT-5.4 Pro measured |
| ARC-AGI | 94.5% | Not measured | Only GPT-5.4 Pro measured |
| ARC-AGI-2 | 83.3% | Not measured | Only GPT-5.4 Pro measured |
| SimpleBench | 74.1% | Not measured | Only GPT-5.4 Pro measured |
| Chess puzzles | 59.0% | Not measured | Only GPT-5.4 Pro measured |
| Neither model has a result on the other 17 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | GPT-5.4 Pro | LFM2.5-24B-A2B | Leader |
|---|---|---|---|
| FrontierMath, tiers 1 to 3 | 82.5% | Not measured | Only GPT-5.4 Pro measured |
| FrontierMath, tier 4 | 58.5% | Not measured | Only GPT-5.4 Pro measured |
| Neither model has a result on the other 11 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | GPT-5.4 Pro | LFM2.5-24B-A2B | Leader |
|---|---|---|---|
| SimpleQA Verified | 46.3% | Not measured | Only GPT-5.4 Pro measured |
| Neither model has a result on the other 17 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 | OpenAI GPT-5.4 Pro | LiquidAI LFM2.5-24B-A2B |
|---|---|---|
| Maker | OpenAI | Liquid |
| Weights | No public weights listed | Open weights |
| Released | March 5, 2026 | October 13, 2026 |
| Context window | 1.05M | 128K |
| Input $/Mtok | $30.00 | $0.05 |
| Output $/Mtok | $180.00 | $0.70 |
| 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 GPT-5.4 Pro better than LFM2.5-24B-A2B for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GPT-5.4 Pro for a larger context window (1.05M against 128K tokens).
Which is cheaper, GPT-5.4 Pro or LFM2.5-24B-A2B?
GPT-5.4 Pro costs $30.00 per million input tokens and $180.00 per million output tokens; LFM2.5-24B-A2B costs $0.05 and $0.70. Cost per solved task is known for neither of them.
Which has the bigger context window, GPT-5.4 Pro or LFM2.5-24B-A2B?
GPT-5.4 Pro, with 1.05M tokens against 128K.
Has any benchmark tested both GPT-5.4 Pro and LFM2.5-24B-A2B?
No benchmark has tested both yet. GPT-5.4 Pro has results on WeirdML, Epoch Capabilities Index and GPQA Diamond (Epoch AI run); LFM2.5-24B-A2B has none yet. Compare them on price and context instead. Data as of October 22, 2026.