LFM2.5-24B-A2B vs Palmyra X5
LFM2.5-24B-A2B costs 8.6x less per output token than Palmyra X5 ($0.70 vs $6.00 per million). Updated October 22, 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
- $6.00
LFM2.5-24B-A2B or Palmyra X5: 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 8.6x cheaper ($0.70 vs $6.00 per million).
No benchmark has tested either model yet, so price and context are the only way to compare them.
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
Palmyra X5
Palmyra X5 takes 1.04M tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
LFM2.5-24B-A2B
LFM2.5-24B-A2B $0.0004, Palmyra X5 $0.0036 per turn.
List prices
At a glance
- Coding index
- LFM2.5-24B-A2B not benchmarked, Palmyra X5 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 Palmyra X5 $6.00 per million output tokens, 8.6x apart.
- Context window
- LFM2.5-24B-A2B takes 128K tokens, Palmyra X5 1.04M.
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.
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 | Writer Palmyra X5 |
|---|---|---|
| Maker | Liquid | Writer |
| Weights | Open weights | No public weights listed |
| Released | October 13, 2026 | January 21, 2026 |
| Context window | 128K | 1.04M |
| Input $/Mtok | $0.05 | $0.60 |
| Output $/Mtok | $0.70 | $6.00 |
| 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 Palmyra X5 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 8.6x cheaper ($0.70 vs $6.00 per million).
Which is cheaper, LFM2.5-24B-A2B or Palmyra X5?
LFM2.5-24B-A2B costs $0.05 per million input tokens and $0.70 per million output tokens; Palmyra X5 costs $0.60 and $6.00. Cost per solved task is known for neither of them.
Which has the bigger context window, LFM2.5-24B-A2B or Palmyra X5?
Palmyra X5, with 1.04M tokens against 128K.
Has any benchmark tested both LFM2.5-24B-A2B and Palmyra X5?
No benchmark has tested either model yet, so price and context are the only way to compare them. Data as of October 22, 2026.