| Signal | LFM2-24B-A2B | Delta | Qwen3.5 Plus 2026-02-15 |
|---|---|---|---|
Capabilities | 17 | -67 | |
Pricing | 100 | +2 | |
Context window size | 72 | -23 | |
Recency | 100 | -- | |
Output Capacity | 20 | -60 | |
| Overall Result | 1 wins | of 5 | 3 wins |
Score History
40
current score
Tied
right now
40
current score
Liquid AI
Alibaba
LFM2-24B-A2B saves you $95.00/month
That's $1140.00/year compared to Qwen3.5 Plus 2026-02-15 at your current usage level of 100K calls/month.
| Metric | LFM2-24B-A2B | Qwen3.5 Plus 2026-02-15 | Winner |
|---|---|---|---|
| Overall Score | 40 | 40 | -- |
| Rank | #183 | #185 | LFM2-24B-A2B |
| Quality Rank | #183 | #185 | LFM2-24B-A2B |
| Adoption Rank | #183 | #185 | LFM2-24B-A2B |
| Parameters | 24B | -- | -- |
| Context Window | 33K | 1000K | Qwen3.5 Plus 2026-02-15 |
| Pricing | $0.03/$0.12/M | $0.26/$1.56/M | -- |
| Signal Scores | |||
| Capabilities | 17 | 83 | Qwen3.5 Plus 2026-02-15 |
| Pricing | 100 | 98 | LFM2-24B-A2B |
| Context window size | 72 | 95 | Qwen3.5 Plus 2026-02-15 |
| Recency | 100 | 100 | LFM2-24B-A2B |
| Output Capacity | 20 | 80 | Qwen3.5 Plus 2026-02-15 |
Our score (0-100) is driven by benchmark performance (90%) from Arena Elo ratings, MMLU, GPQA, HumanEval, SWE-bench, and 15+ standardized evaluations. Capabilities and context window serve as tiebreakers (10%). Learn more about our methodology.
Scores 40/100 (rank #183), placing it in the top 37% of all 290 models tracked.
Scores 40/100 (rank #185), placing it in the top 37% of all 290 models tracked.
With only a 0-point gap, these models are in the same performance tier. The practical difference in output quality is minimal - your choice should depend on pricing, latency requirements, and specific feature needs.
LFM2-24B-A2B offers 92% better value per quality point. At 1M tokens/day, you'd spend $2.25/month with LFM2-24B-A2B vs $27.30/month with Qwen3.5 Plus 2026-02-15 - a $25.05 monthly difference.
Both models have comparable response speeds. For most applications, the latency difference is negligible.
When latency matters most: Interactive chatbots, IDE code completion, real-time translation, and user-facing applications where response time directly impacts experience. For batch processing, background summarization, or offline analysis, latency is less critical.
Code generation & review
Higher benchmark score (0/100) indicates stronger performance on coding tasks like generating functions, debugging, and refactoring
Customer support chatbot
Faster response time (speed score 0/100) is critical for user-facing chat. LFM2-24B-A2B also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (1000K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($0.12/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (40/100) correlates with better nuance, coherence, and style in long-form content
Image understanding & OCR
Supports vision input - can analyze screenshots, diagrams, photos, and scanned documents directly
LFM2-24B-A2B and Qwen3.5 Plus 2026-02-15 are extremely close in overall performance (only 0 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.
Best for Quality
LFM2-24B-A2B
Marginally better benchmark scores; both are excellent
Best for Cost
LFM2-24B-A2B
92% lower pricing; better value at scale
Best for Reliability
LFM2-24B-A2B
Higher uptime and faster response speeds
Best for Prototyping
LFM2-24B-A2B
Stronger community support and better developer experience
Best for Production
LFM2-24B-A2B
Wider enterprise adoption and proven at scale
by Liquid AI
| Capability | LFM2-24B-A2B | Qwen3.5 Plus 2026-02-15 |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Callingdiffers | ||
| Streaming | ||
| JSON Modediffers | ||
| Reasoningdiffers | ||
| Web Search | ||
| Image Output |
Liquid AI
Alibaba
LFM2-24B-A2B saves you $2.14/month
That's 92% cheaper than Qwen3.5 Plus 2026-02-15 at 1,000 tokens/request and 100 requests/day.
Assumes 60% input / 40% output token ratio per request. Actual costs may vary based on your usage pattern.
| Parameter | LFM2-24B-A2B | Qwen3.5 Plus 2026-02-15 |
|---|---|---|
| Context Window | 33K | 1M |
| Max Output Tokens | -- | 65,536 |
| Open Source | Yes | No |
| Created | Feb 25, 2026 | Feb 16, 2026 |
Both LFM2-24B-A2B and Qwen3.5 Plus 2026-02-15 score 40/100, making them extremely close competitors. Choose based on pricing, provider ecosystem, or specific capability requirements.
LFM2-24B-A2B is ranked #183 and Qwen3.5 Plus 2026-02-15 is ranked #185 out of 290+ AI models. Rankings use a composite score combining benchmark performance (90%) from MMLU, GPQA, HumanEval, SWE-bench, and 15+ standardized evaluations, with capabilities and context window as tiebreakers (10%). Scores update hourly.
LFM2-24B-A2B is cheaper at $0.12/M output tokens vs Qwen3.5 Plus 2026-02-15's $1.56/M output tokens - 13.0x more expensive. Input token pricing: LFM2-24B-A2B at $0.03/M vs Qwen3.5 Plus 2026-02-15 at $0.26/M.
Qwen3.5 Plus 2026-02-15 has a larger context window of 1,000,000 tokens compared to LFM2-24B-A2B's 32,768 tokens. A larger context window means the model can process longer documents and conversations.