LLM Comparison
LFM2.5-1.2B-Instruct vs Maple-Preview
Side-by-side specs, pricing & capabilities · Updated September 2026
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2/6 modelsSame tier:
| Organization | ||
| OpenTools Score | 45 | |
| Family | LFM2.5-1.2B-Instruct | Maple |
| Status | Current | Current |
| Release Date | Jan 2026 | Aug 2026 |
| Context Window | 33K tokens | 131K tokens |
| Input Price | — | — |
| Output Price | — | — |
| Pricing Notes | Free tier available on OpenRouter with rate limits | Open-source model card; no hosted API pricing found in the official source. Local inference costs depend on user hardware and runtime. |
| Capabilities | textcode | textreasoningcodeon-device-inference |
| Max Output | — | 131K tokens |
| API Identifier | liquid/lfm-2.5-1.2b-instruct:free | deepgrove/maple-preview |
| Benchmarks | ||
| GPQA Diamond | 32.6263artificial-analysis | 73.5DeepGrove model card |
| LiveCodeBench v6 | — | 75.1DeepGrove model card |
| AIME 2026 | — | 87.5DeepGrove model card |
| HMMT 2026 | — | 78.8DeepGrove model card |
| View LFM2.5-1.2B-Instruct | View Maple-Preview | |
Liquid AI
LFM2.5-1.2B-Instruct
LFM2.5-1.2B-Instruct is a large language model from Liquid AI. Supports up to 32,768 token context window. Available free with rate limits on OpenRouter.
DeepGrove
Maple-Preview
Maple-Preview is DeepGrove’s open-source 20B-A1B ternary-weight reasoning LLM for efficient on-device inference. The model card reports 20.2B total parameters, 1.49B active parameters, a 131,072-token context window, and 5.31 GB checkpoint size.
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