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DeepSeek: DeepSeek V3.2 vs Inference.net: Schematron V2 Small

Neither wins outright: DeepSeek: DeepSeek V3.2 is the pick when you need tool / function calling, Inference.net: Schematron V2 Small when cost matters at scale.

Key numbers

SpecDeepSeek: DeepSeek V3.2Inference.net: Schematron V2 Small
ProviderDeepSeekInference.net
Input price (per 1M tokens)$0.28$0.05
Output price (per 1M tokens)$0.42$0.23
Blended price (3:1 input/output)$0.32$0.10
Cheaper than … of all models we track63%82%
Context window164K tokens (~246 pages)128K tokens (~192 pages)
Larger context than … of all models35%14%
Max output per response66K tokens (~49,200 words)4K tokens (~3,100 words)
Input typestexttext
Output typestexttext
Free variantNoNo
Listed since2025-12-012026-09-12
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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 V3.2Inference.net: Schematron V2 SmallDifference
Customer-support chatbot
50,000 conversations — each a 6-turn conversation (1,500 in / 400 out tokens)
$29.40$8.35Inference.net: Schematron V2 Small saves $21.05
RAG search over documents
20,000 questions — each a question answered from ~8 retrieved passages (6,000 in / 500 out tokens)
$37.80$8.30Inference.net: Schematron V2 Small saves $29.50
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)
$38.64$8.76Inference.net: Schematron V2 Small saves $29.88
Batch summarisation
10,000 documents — each a 6,000-word report summarised to a page (8,000 in / 600 out tokens)
$24.92$5.38Inference.net: Schematron V2 Small saves $19.54
Long-document analysis
500 documents — each a 150-page contract or codebase read in one pass (100,000 in / 2,000 out tokens)
$14.42$2.73Inference.net: Schematron V2 Small saves $11.69

Capabilities side by side

CapabilityDeepSeek: DeepSeek V3.2Inference.net: Schematron V2 SmallWhat it lets you do
Tool / function calling✓ Yes—call your APIs and run agent loops
Structured output (JSON schema)✓ Yes✓ Yesreturn JSON that validates against your schema
Reasoning / thinking mode✓ 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✓ Yesrepeat 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

DateModelInput / 1MOutput / 1M
2026-10-18DeepSeek: DeepSeek V3.2$0.28$0.42
2026-10-11DeepSeek: DeepSeek V3.2$0.26$0.80
2026-10-08DeepSeek: DeepSeek V3.2$0.26$0.42
2026-09-28DeepSeek: DeepSeek V3.2$0.28$0.42
2026-08-31DeepSeek: DeepSeek V3.2$0.27$0.40
2026-08-22DeepSeek: DeepSeek V3.2$0.26$0.38
2026-08-10DeepSeek: DeepSeek V3.2$0.27$0.40
2026-08-08DeepSeek: DeepSeek V3.2$0.26$0.38

Which should you choose?

Choose DeepSeek: DeepSeek V3.2 if…

  • you need tool / function calling — to call your APIs and run agent loops; Inference.net: Schematron V2 Small does not advertise it
  • you need reasoning / thinking mode — to spend extra tokens thinking before answering hard problems; Inference.net: Schematron V2 Small does not advertise it
  • you need log-probabilities — to read token confidence for classification and scoring; Inference.net: Schematron V2 Small does not advertise it
  • you generate long outputs in one go — up to 66K tokens (about 49,200 words) per response

Choose Inference.net: Schematron V2 Small if…

  • cost matters at scale — it is 70% cheaper on a typical 3:1 input/output mix ($8.35 vs $29.40 a month for 50,000 support chats)
  • you want the newer model — released 2026-09-12, 10 months after the other

Frequently asked questions

Is DeepSeek: DeepSeek V3.2 better than Inference.net: Schematron V2 Small?

Neither wins outright: DeepSeek: DeepSeek V3.2 is the pick when you need tool / function calling, Inference.net: Schematron V2 Small when cost matters at scale. In short: DeepSeek: DeepSeek V3.2 when you need tool / function calling, you need reasoning / thinking mode, you need log-probabilities, you generate long outputs in one go; Inference.net: Schematron V2 Small when cost matters at scale, you want the newer model.

Which is cheaper, DeepSeek: DeepSeek V3.2 or Inference.net: Schematron V2 Small?

Inference.net: Schematron V2 Small is cheaper: $0.10 vs $0.32 per 1M tokens at a typical 3:1 input/output mix, 70% less. For 50,000 support conversations a month that is $8.35 against $29.40.

How much do DeepSeek: DeepSeek V3.2 and Inference.net: Schematron V2 Small cost per million tokens?

DeepSeek: DeepSeek V3.2 costs $0.28 per 1M input tokens and $0.42 per 1M output tokens; Inference.net: Schematron V2 Small costs $0.05 input and $0.23 output. Output tokens are billed separately, so long answers shift the gap.

Which has the bigger context window, DeepSeek: DeepSeek V3.2 or Inference.net: Schematron V2 Small?

DeepSeek: DeepSeek V3.2: 164K tokens, about 246 pages, against 128K (about 192 pages) for Inference.net: Schematron V2 Small.

Do DeepSeek: DeepSeek V3.2 and Inference.net: Schematron V2 Small support function calling and JSON output?

Tool calling — DeepSeek: DeepSeek V3.2: yes, Inference.net: Schematron V2 Small: not advertised. JSON-schema structured output — DeepSeek: DeepSeek V3.2: yes, Inference.net: Schematron V2 Small: yes.

Can DeepSeek: DeepSeek V3.2 or Inference.net: Schematron V2 Small read images?

Neither accepts image input — both are text-in models.

Is DeepSeek: DeepSeek V3.2 or Inference.net: Schematron V2 Small free to use?

No free variant is listed for either; both are pay-per-token.

What is the maximum output length of DeepSeek: DeepSeek V3.2 and Inference.net: Schematron V2 Small?

DeepSeek: DeepSeek V3.2 can write up to 66K tokens (about 49,200 words) per response; Inference.net: Schematron V2 Small up to 4K (about 3,100 words).

When were DeepSeek: DeepSeek V3.2 and Inference.net: Schematron V2 Small released?

DeepSeek: DeepSeek V3.2 was listed on 2025-12-01; Inference.net: Schematron V2 Small on 2026-09-12.

Has the price of DeepSeek: DeepSeek V3.2 or Inference.net: Schematron V2 Small changed?

DeepSeek: DeepSeek V3.2: input price raised 8% ($0.26 → $0.28/1M), output price cut 48% ($0.80 → $0.42/1M) on 2026-10-18 (10 price changes since 2026-03-10). Inference.net: Schematron V2 Small: price unchanged since we started tracking it on 2026-09-12.

About the two models

DeepSeek

DeepSeek: DeepSeek V3.2

DeepSeek-V3.2 is a large language model designed to harmonize high computational efficiency with strong reasoning and agentic tool-use performance. It introduces DeepSeek Sparse Attention (DSA), a fine-grained sparse attention mechanism...

Full DeepSeek: DeepSeek V3.2 specs →

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