Neither wins outright: DeepSeek: DeepSeek V3.2 Exp is the pick when cost matters at scale, LiquidAI: LFM2.5-2.6B when you need seed (reproducible sampling).
| Spec | DeepSeek: DeepSeek V3.2 Exp | LiquidAI: LFM2.5-2.6B |
|---|---|---|
| Provider | DeepSeek | Liquid |
| Input price (per 1M tokens) | $0.27 | $0.35 |
| Output price (per 1M tokens) | $0.41 | $0.50 |
| Blended price (3:1 input/output) | $0.30 | $0.39 |
| Cheaper than … of all models we track | 62% | 58% |
| Context window | 164K tokens (~246 pages) | 128K tokens (~192 pages) |
| Larger context than … of all models | 35% | 14% |
| Max output per response | 147K tokens (~110,600 words) | 8K tokens (~6,100 words) |
| Input types | text | text |
| Output types | text | text |
| Free variant | No | Yes |
| Listed since | 2025-09-29 | 2026-08-11 |
Monthly cost at list price for five common workloads. Token counts per unit are stated so you can scale them to your own traffic. A workload that does not fit a model's context window is marked rather than priced.
| Workload (per month) | DeepSeek: DeepSeek V3.2 Exp | LiquidAI: LFM2.5-2.6B | Difference |
|---|---|---|---|
| Customer-support chatbot 50,000 conversations — each a 6-turn conversation (1,500 in / 400 out tokens) | $28.45 | $36.25 | DeepSeek: DeepSeek V3.2 Exp saves $7.80 |
| RAG search over documents 20,000 questions — each a question answered from ~8 retrieved passages (6,000 in / 500 out tokens) | $36.50 | $47.00 | DeepSeek: DeepSeek V3.2 Exp saves $10.50 |
| Coding / tool-using agent 2,000 tasks — each a multi-step task with tool calls and file context (60,000 in / 6,000 out tokens) | $37.32 | $48.00 | DeepSeek: DeepSeek V3.2 Exp saves $10.68 |
| Batch summarisation 10,000 documents — each a 6,000-word report summarised to a page (8,000 in / 600 out tokens) | $24.06 | $31.00 | DeepSeek: DeepSeek V3.2 Exp saves $6.94 |
| Long-document analysis 500 documents — each a 150-page contract or codebase read in one pass (100,000 in / 2,000 out tokens) | $13.91 | $18.00 | DeepSeek: DeepSeek V3.2 Exp saves $4.09 |
| Capability | DeepSeek: DeepSeek V3.2 Exp | LiquidAI: LFM2.5-2.6B | What it lets you do |
|---|---|---|---|
| Tool / function calling | ✓ Yes | ✓ Yes | call your APIs and run agent loops |
| Structured output (JSON schema) | ✓ Yes | ✓ Yes | return JSON that validates against your schema |
| Reasoning / thinking mode | ✓ Yes | ✓ Yes | spend extra tokens thinking before answering hard problems |
| Image input | — | — | read screenshots, charts and scanned pages |
| Audio input | — | — | take speech or audio directly |
| File / PDF input | — | — | accept documents without your own parsing step |
| Image output | — | — | generate images, not just text |
| Built-in web search | — | — | answer from live web results |
| Seed (reproducible sampling) | — | ✓ Yes | repeat a generation for tests and evals |
| Log-probabilities | — | ✓ Yes | read token confidence for classification and scoring |
From each model's published parameters and input/output types. “—” means not advertised, not proven absent.
| Date | Model | Input / 1M | Output / 1M |
|---|---|---|---|
| 2026-09-30 | DeepSeek: DeepSeek V3.2 Exp | $0.27 | $0.41 |
| 2026-09-29 | DeepSeek: DeepSeek V3.2 Exp | $0.13 | $0.20 |
Neither wins outright: DeepSeek: DeepSeek V3.2 Exp is the pick when cost matters at scale, LiquidAI: LFM2.5-2.6B when you need seed (reproducible sampling). In short: DeepSeek: DeepSeek V3.2 Exp when cost matters at scale, you generate long outputs in one go; LiquidAI: LFM2.5-2.6B when you need seed (reproducible sampling), you need log-probabilities, you want to prototype at zero cost, you want the newer model.
DeepSeek: DeepSeek V3.2 Exp is cheaper: $0.30 vs $0.39 per 1M tokens at a typical 3:1 input/output mix, 21% less. For 50,000 support conversations a month that is $28.45 against $36.25.
DeepSeek: DeepSeek V3.2 Exp costs $0.27 per 1M input tokens and $0.41 per 1M output tokens; LiquidAI: LFM2.5-2.6B costs $0.35 input and $0.50 output. Output tokens are billed separately, so long answers shift the gap.
DeepSeek: DeepSeek V3.2 Exp: 164K tokens, about 246 pages, against 128K (about 192 pages) for LiquidAI: LFM2.5-2.6B.
Tool calling — DeepSeek: DeepSeek V3.2 Exp: yes, LiquidAI: LFM2.5-2.6B: yes. JSON-schema structured output — DeepSeek: DeepSeek V3.2 Exp: yes, LiquidAI: LFM2.5-2.6B: yes.
Neither accepts image input — both are text-in models.
LiquidAI: LFM2.5-2.6B has a free variant (liquid/lfm-2.5-2.6b:free). Free variants usually carry tighter rate limits.
DeepSeek: DeepSeek V3.2 Exp can write up to 147K tokens (about 110,600 words) per response; LiquidAI: LFM2.5-2.6B up to 8K (about 6,100 words).
DeepSeek: DeepSeek V3.2 Exp was listed on 2025-09-29; LiquidAI: LFM2.5-2.6B on 2026-08-11.
DeepSeek: DeepSeek V3.2 Exp: input price raised 50% ($0.13 → $0.27/1M), output price raised 51% ($0.20 → $0.41/1M) on 2026-09-30 (2 price changes since 2026-03-10). LiquidAI: LFM2.5-2.6B: price unchanged since we started tracking it on 2026-10-25.
DeepSeek-V3.2-Exp is an experimental large language model released by DeepSeek as an intermediate step between V3.1 and future architectures. It introduces DeepSeek Sparse Attention (DSA), a fine-grained sparse attention mechanism...
Full DeepSeek: DeepSeek V3.2 Exp specs →LFM2.5-2.6B is a compact reasoning model from Liquid AI. It is suited for agent workflows, data extraction, RAG, and long-context processing. Liquid advises against using it for agentic coding or...
Full LiquidAI: LFM2.5-2.6B specs →