Google: Gemini 2.5 Flash (batch) vs NVIDIA: Nemotron 3.5 Super VL

Neither wins outright: Google: Gemini 2.5 Flash (batch) is the pick when you need audio input, NVIDIA: Nemotron 3.5 Super VL when cost matters at scale.

Key numbers

SpecGoogle: Gemini 2.5 Flash (batch)NVIDIA: Nemotron 3.5 Super VL
ProviderGoogleNvidia
Input price (per 1M tokens)$0.15$0.15
Output price (per 1M tokens)$1.25$0.50
Blended price (3:1 input/output)$0.42$0.24
Cheaper than … of all models we track57%67%
Context window1.0M tokens (~1,573 pages)1.0M tokens (~1,573 pages)
Larger context than … of all models81%81%
Max output per response66K tokens (~49,200 words)236K tokens (~176,900 words)
Input typesfile, image, text, audio, videotext, image, video
Output typestexttext
Free variantNoYes
Listed since2025-06-172026-10-15

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)Google: Gemini 2.5 Flash (batch)NVIDIA: Nemotron 3.5 Super VLDifference
Customer-support chatbot
50,000 conversations — each a 6-turn conversation (1,500 in / 400 out tokens)
$36.25$21.25NVIDIA: Nemotron 3.5 Super VL saves $15.00
RAG search over documents
20,000 questions — each a question answered from ~8 retrieved passages (6,000 in / 500 out tokens)
$30.50$23.00NVIDIA: Nemotron 3.5 Super VL saves $7.50
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)
$33.00$24.00NVIDIA: Nemotron 3.5 Super VL saves $9.00
Batch summarisation
10,000 documents — each a 6,000-word report summarised to a page (8,000 in / 600 out tokens)
$19.50$15.00NVIDIA: Nemotron 3.5 Super VL saves $4.50
Long-document analysis
500 documents — each a 150-page contract or codebase read in one pass (100,000 in / 2,000 out tokens)
$8.75$8.00NVIDIA: Nemotron 3.5 Super VL saves $0.75

Capabilities side by side

CapabilityGoogle: Gemini 2.5 Flash (batch)NVIDIA: Nemotron 3.5 Super VLWhat it lets you do
Tool / function calling✓ Yes✓ Yescall your APIs and run agent loops
Structured output (JSON schema)✓ Yes✓ Yesreturn JSON that validates against your schema
Reasoning / thinking mode✓ Yes✓ Yesspend extra tokens thinking before answering hard problems
Image input✓ Yes✓ Yesread screenshots, charts and scanned pages
Audio input✓ Yes—take speech or audio directly
File / PDF input✓ Yes—accept documents without your own parsing step
Image output——generate images, not just text
Built-in web search✓ Yes—answer from live web results
Seed (reproducible sampling)✓ Yes✓ Yesrepeat a generation for tests and evals
Log-probabilities—✓ Yesread token confidence for classification and scoring

From each model's published parameters and input/output types. “—” means not advertised, not proven absent.

Price history

Which should you choose?

Choose Google: Gemini 2.5 Flash (batch) if…

  • you need audio input — to take speech or audio directly; NVIDIA: Nemotron 3.5 Super VL does not advertise it
  • you need file / PDF input — to accept documents without your own parsing step; NVIDIA: Nemotron 3.5 Super VL does not advertise it
  • you need built-in web search — to answer from live web results; NVIDIA: Nemotron 3.5 Super VL does not advertise it

Choose NVIDIA: Nemotron 3.5 Super VL if…

  • cost matters at scale — it is 44% cheaper on a typical 3:1 input/output mix ($21.25 vs $36.25 a month for 50,000 support chats)
  • you need log-probabilities — to read token confidence for classification and scoring; Google: Gemini 2.5 Flash (batch) does not advertise it
  • you generate long outputs in one go — up to 236K tokens (about 176,900 words) per response
  • you want to prototype at zero cost — a free variant is listed
  • you want the newer model — released 2026-10-15, 16 months after the other

Frequently asked questions

Is Google: Gemini 2.5 Flash (batch) better than NVIDIA: Nemotron 3.5 Super VL?

Neither wins outright: Google: Gemini 2.5 Flash (batch) is the pick when you need audio input, NVIDIA: Nemotron 3.5 Super VL when cost matters at scale. In short: Google: Gemini 2.5 Flash (batch) when you need audio input, you need file / PDF input, you need built-in web search; NVIDIA: Nemotron 3.5 Super VL when cost matters at scale, you need log-probabilities, you generate long outputs in one go, you want to prototype at zero cost, you want the newer model.

Which is cheaper, Google: Gemini 2.5 Flash (batch) or NVIDIA: Nemotron 3.5 Super VL?

NVIDIA: Nemotron 3.5 Super VL is cheaper: $0.24 vs $0.42 per 1M tokens at a typical 3:1 input/output mix, 44% less. For 50,000 support conversations a month that is $21.25 against $36.25.

How much do Google: Gemini 2.5 Flash (batch) and NVIDIA: Nemotron 3.5 Super VL cost per million tokens?

Google: Gemini 2.5 Flash (batch) costs $0.15 per 1M input tokens and $1.25 per 1M output tokens; NVIDIA: Nemotron 3.5 Super VL costs $0.15 input and $0.50 output. Output tokens are billed separately, so long answers shift the gap.

Which has the bigger context window, Google: Gemini 2.5 Flash (batch) or NVIDIA: Nemotron 3.5 Super VL?

Both take 1.0M tokens per request — roughly 1,573 pages of text.

Do Google: Gemini 2.5 Flash (batch) and NVIDIA: Nemotron 3.5 Super VL support function calling and JSON output?

Tool calling — Google: Gemini 2.5 Flash (batch): yes, NVIDIA: Nemotron 3.5 Super VL: yes. JSON-schema structured output — Google: Gemini 2.5 Flash (batch): yes, NVIDIA: Nemotron 3.5 Super VL: yes.

Can Google: Gemini 2.5 Flash (batch) or NVIDIA: Nemotron 3.5 Super VL read images?

Yes, both accept image input.

Is Google: Gemini 2.5 Flash (batch) or NVIDIA: Nemotron 3.5 Super VL free to use?

NVIDIA: Nemotron 3.5 Super VL has a free variant (nvidia/nemotron-3.5-super-vl:free). Free variants usually carry tighter rate limits.

What is the maximum output length of Google: Gemini 2.5 Flash (batch) and NVIDIA: Nemotron 3.5 Super VL?

Google: Gemini 2.5 Flash (batch) can write up to 66K tokens (about 49,200 words) per response; NVIDIA: Nemotron 3.5 Super VL up to 236K (about 176,900 words).

When were Google: Gemini 2.5 Flash (batch) and NVIDIA: Nemotron 3.5 Super VL released?

Google: Gemini 2.5 Flash (batch) was listed on 2025-06-17; NVIDIA: Nemotron 3.5 Super VL on 2026-10-15.

About the two models

Compare Google: Gemini 2.5 Flash (batch) with other models

Compare NVIDIA: Nemotron 3.5 Super VL with other models

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