Choose DeepSeek: DeepSeek V3.1 Terminus (exacto) if…
No advantage on the data we track — pick it for provider preference or output quality on your own prompts.
DeepSeek: DeepSeek V3.1 Terminus (exacto) vs LiquidAI: LFM2.5-24B-A2B
LiquidAI: LFM2.5-24B-A2B comes out ahead on the data we track: 3 advantages and none for DeepSeek: DeepSeek V3.1 Terminus (exacto).
Key numbers
| Spec | DeepSeek: DeepSeek V3.1 Terminus (exacto) | LiquidAI: LFM2.5-24B-A2B |
|---|---|---|
| Provider | DeepSeek | Liquid |
| Input price (per 1M tokens) | $0.21 | $0.05 |
| Output price (per 1M tokens) | $0.79 | $0.70 |
| Blended price (3:1 input/output) | $0.35 | $0.21 |
| Cheaper than … of all models we track | 61% | 68% |
| Context window | 164K tokens (~246 pages) | 128K tokens (~192 pages) |
| Larger context than … of all models | 36% | 14% |
| Max output per response | n/a | 8K tokens (~6,100 words) |
| Input types | text | text |
| Output types | text | text |
| Free variant | No | No |
| Listed since | 2025-09-22 | 2026-10-13 |
What it costs for real workloads
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 V3.1 Terminus (exacto) | LiquidAI: LFM2.5-24B-A2B | Difference |
|---|---|---|---|
| Customer-support chatbot 50,000 conversations — each a 6-turn conversation (1,500 in / 400 out tokens) | $31.55 | $17.75 | LiquidAI: LFM2.5-24B-A2B saves $13.80 |
| RAG search over documents 20,000 questions — each a question answered from ~8 retrieved passages (6,000 in / 500 out tokens) | $33.10 | $13.00 | LiquidAI: LFM2.5-24B-A2B saves $20.10 |
| 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) | $34.68 | $14.40 | LiquidAI: LFM2.5-24B-A2B saves $20.28 |
| Batch summarisation 10,000 documents — each a 6,000-word report summarised to a page (8,000 in / 600 out tokens) | $21.54 | $8.20 | LiquidAI: LFM2.5-24B-A2B saves $13.34 |
| Long-document analysis 500 documents — each a 150-page contract or codebase read in one pass (100,000 in / 2,000 out tokens) | $11.29 | $3.20 | LiquidAI: LFM2.5-24B-A2B saves $8.09 |
Capabilities side by side
| Capability | DeepSeek: DeepSeek V3.1 Terminus (exacto) | LiquidAI: LFM2.5-24B-A2B | 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 | ✓ 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.
Price history
- DeepSeek: DeepSeek V3.1 Terminus (exacto): price unchanged since we started tracking it on 2026-03-10.
- LiquidAI: LFM2.5-24B-A2B: price unchanged since we started tracking it on 2026-10-14.
Which should you choose?
Choose LiquidAI: LFM2.5-24B-A2B if…
- cost matters at scale — it is 40% cheaper on a typical 3:1 input/output mix ($17.75 vs $31.55 a month for 50,000 support chats)
- you need log-probabilities — to read token confidence for classification and scoring; DeepSeek: DeepSeek V3.1 Terminus (exacto) does not advertise it
- you want the newer model — released 2026-10-13, 13 months after the other
Frequently asked questions
Is DeepSeek: DeepSeek V3.1 Terminus (exacto) better than LiquidAI: LFM2.5-24B-A2B?
LiquidAI: LFM2.5-24B-A2B comes out ahead on the data we track: 3 advantages and none for DeepSeek: DeepSeek V3.1 Terminus (exacto).
Which is cheaper, DeepSeek: DeepSeek V3.1 Terminus (exacto) or LiquidAI: LFM2.5-24B-A2B?
LiquidAI: LFM2.5-24B-A2B is cheaper: $0.21 vs $0.35 per 1M tokens at a typical 3:1 input/output mix, 40% less. For 50,000 support conversations a month that is $17.75 against $31.55.
How much do DeepSeek: DeepSeek V3.1 Terminus (exacto) and LiquidAI: LFM2.5-24B-A2B cost per million tokens?
DeepSeek: DeepSeek V3.1 Terminus (exacto) costs $0.21 per 1M input tokens and $0.79 per 1M output tokens; LiquidAI: LFM2.5-24B-A2B costs $0.05 input and $0.70 output. Output tokens are billed separately, so long answers shift the gap.
Which has the bigger context window, DeepSeek: DeepSeek V3.1 Terminus (exacto) or LiquidAI: LFM2.5-24B-A2B?
DeepSeek: DeepSeek V3.1 Terminus (exacto): 164K tokens, about 246 pages, against 128K (about 192 pages) for LiquidAI: LFM2.5-24B-A2B.
Do DeepSeek: DeepSeek V3.1 Terminus (exacto) and LiquidAI: LFM2.5-24B-A2B support function calling and JSON output?
Tool calling — DeepSeek: DeepSeek V3.1 Terminus (exacto): yes, LiquidAI: LFM2.5-24B-A2B: yes. JSON-schema structured output — DeepSeek: DeepSeek V3.1 Terminus (exacto): yes, LiquidAI: LFM2.5-24B-A2B: yes.
Can DeepSeek: DeepSeek V3.1 Terminus (exacto) or LiquidAI: LFM2.5-24B-A2B read images?
Neither accepts image input — both are text-in models.
Is DeepSeek: DeepSeek V3.1 Terminus (exacto) or LiquidAI: LFM2.5-24B-A2B free to use?
No free variant is listed for either; both are pay-per-token.
When were DeepSeek: DeepSeek V3.1 Terminus (exacto) and LiquidAI: LFM2.5-24B-A2B released?
DeepSeek: DeepSeek V3.1 Terminus (exacto) was listed on 2025-09-22; LiquidAI: LFM2.5-24B-A2B on 2026-10-13.
About the two models
DeepSeek: DeepSeek V3.1 Terminus (exacto)
DeepSeek-V3.1 Terminus is an update to [DeepSeek V3.1](/deepseek/deepseek-chat-v3.1) that maintains the model's original capabilities while addressing issues reported by users, including language consistency and agent capabilities, further optimizing the model's performance in coding and search agents. It is a large hybrid reasoning model (671B parameters, 37B active) that supports both thinking and non-thinking modes. It extends the DeepSeek-V3 base with a two-phase long-context training process, reaching up to 128K tokens, and uses FP8 microscaling for efficient inference. Users can control the reasoning behaviour with the `reasoning` `enabled` boolean. [Learn more in our docs](https://openrouter.ai/docs/use-cases/reasoning-tokens#enable-reasoning-with-default-config) The model improves tool use, code generation, and reasoning efficiency, achieving performance comparable to DeepSeek-R1 on difficult benchmarks while responding more quickly. It supports structured tool calling, code agents, and search agents, making it suitable for research, coding, and agentic workflows.
Full DeepSeek: DeepSeek V3.1 Terminus (exacto) specs →LiquidAI: LFM2.5-24B-A2B
LFM2.5-24B-A2B is a mixture-of-experts reasoning model from Liquid AI with 24B total and 2.45B active parameters. It always reasons before answering and is built for agents that call tools. Liquid...
Full LiquidAI: LFM2.5-24B-A2B specs →