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DeepSeek V3.1 (Reasoning) vs Nemotron 3 Ultra

Updated October 14, 2026. Rank says Nemotron 3 Ultra is ahead. Price, access, and your workload can each overturn that. Public scores include evidence status and uncertainty.

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Decision reading

Nemotron 3 Ultra has the higher public point estimate, 47.25 versus 39.24. Their conditional score ranges overlap. These ranges do not establish rank confidence. 3 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.

Model A
DeepSeek logo

DeepSeek

39.24/100

Estimated · Public rank #137

Conditional range 29.5–49.0

Model B
NVIDIA logo

NVIDIA

47.25/100

Estimated · Public rank #105

Conditional range 32.9–61.6

Shared results
3
DeepSeek V3.1 (Reasoning) only
3
Nemotron 3 Ultra only
21
Like-for-like categories
0 / 8
Estimated: DeepSeek V3.1 (Reasoning) and Nemotron 3 Ultra. Conditional ranges do not establish rank confidence.How the comparison works

Which one for your work

Recommendations appear only when a shared evidence basis or an explicit operating constraint supports the call. Secondary and unsupported use cases stay disclosed below the initial list.

  • Long documents

    Prompts that approach the documented context limit

    Nemotron 3 Ultra

    Nemotron 3 Ultra has the larger documented context window.

    Confidence: documented
Show secondary and unsupported calls
  • Coding work

    Code generation, repair, and software-engineering tasks

    Not enough matched evidence

    DeepSeek V3.1 (Reasoning) is not ranked on the public lane for coding, so no winner is named for coding.

    Confidence: limited
  • Agentic work

    Tool use, computer use, and multi-step task completion

    Not enough matched evidence

    DeepSeek V3.1 (Reasoning) is not ranked on the public lane for agentic, so no winner is named for agentic.

    Confidence: limited
  • Chat turn cost

    1K fresh input + 500 output tokens

    Not enough matched evidence

    A complete comparable API-rate estimate is not available for both models.

    Confidence: listed-rates
  • Cache-heavy agent loop cost

    200K cached + 20K fresh input + 10K output tokens

    Not enough matched evidence

    The page does not recommend a cost winner because at least one model cannot fit the stated workload in one request. DeepSeek V3.1 (Reasoning) does not fit this workload in one request. DeepSeek V3.1 (Reasoning) has no comparable published API token rate. Nemotron 3 Ultra has no comparable published API token rate.

    Confidence: listed-rates
  • Repository review cost

    50K fresh input + 3K output tokens

    Not enough matched evidence

    A complete comparable API-rate estimate is not available for both models.

    Confidence: listed-rates

Which one for a specific job

Choose a job from the LLM Selector's task catalog to see the category row it rests on, under the same basis rules as the table below. A directional row stays directional; choosing a job never creates a winner.

The same task catalog as the LLM Selector. Each job names the evidence surface it rests on; nothing here adds a new score.

—DeepSeek V3.1 (Reasoning)21.9Nemotron 3 Ultra

Not comparable · BenchAlign v5.8

The coding row is not comparable on the public lane: at least one model is not measured or not ranked there.

Coding scores combine specific tasks and setups. Match the editor, harness, and effort to your workflow.

Same basis rules as the category table below

What is actually comparable

Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.

2 categories rest on Estimated evidence or different evidence sets. Those rows remain visible for coverage context but do not name a winner.

Shape of the matched evidence

Only shared public evidence is shown. Sparse evidence stays a ruled list rather than being closed into a radar shape.

Too few matched category axes support a radar. The ruled list below shows only shared benchmark results; positions use each benchmark’s normalized display scale when available.

Bars run 0–100 on each benchmark’s normalized display scale

Category results, on a stated basis

Each row shows the public-lane category score for both models: the BenchAlign v5.8 lane for agentic, coding, and knowledge, and the weighted public rows elsewhere, with the same rank each model page reports. A row is like-for-like only when both scores rest on Supported evidence or the same weighted set. Directional and not-comparable rows remain visible, but they never receive a winner.

Knowledge

Directional only
DeepSeek V3.1 (Reasoning)
40.6
Supported · #114/181
Nemotron 3 Ultra
50.4
Estimated · #77/181
Basis
BenchAlign v5.8 lane · 3 vs 7 public rows
Reading
Directional only

Instruction following

Directional only
DeepSeek V3.1 (Reasoning)
48.4
#91/144
Nemotron 3 Ultra
92.1
#20/144
Basis
Provisional lane · 0 vs 1 weighted rows
Reading
Directional only

Agentic

Not comparable
DeepSeek V3.1 (Reasoning)
Not ranked
Nemotron 3 Ultra
28.2
Supported · #95/125
Basis
BenchAlign v5.8 lane · 0 vs 6 public rows
Reading
Not comparable

Coding

Not comparable
DeepSeek V3.1 (Reasoning)
Not ranked
Nemotron 3 Ultra
21.9
Supported · #115/149
Basis
BenchAlign v5.8 lane · 1 vs 7 public rows
Reading
Not comparable

Reasoning

Not comparable
DeepSeek V3.1 (Reasoning)
64.8
Unranked · 2 rankable rows
Nemotron 3 Ultra
70.8
#20/29
Basis
Provisional lane · 0 vs 1 weighted rows
Reading
Not comparable

Multimodal

Not comparable
DeepSeek V3.1 (Reasoning)
Not ranked
Nemotron 3 Ultra
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Multilingual

Not comparable
DeepSeek V3.1 (Reasoning)
Not ranked
Nemotron 3 Ultra
89.2
#7/17
Basis
Provisional lane · 0 vs 1 weighted rows
Reading
Not comparable

Math

Not comparable
DeepSeek V3.1 (Reasoning)
Not ranked
Nemotron 3 Ultra
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Ranks count the models scored in each category’s lane, so the agentic, coding, and knowledge denominators (BenchAlign v5.8) differ from the provisional-lane categories. Unranked scores sit on the provisional lane’s scale but never name a winner. Like-for-like rows within 0.5 points read as a practical tie.

Supported evidence per lane · bars run 0–100Methodology

What each workload costs

Three fixed token mixes turn per-token rates into comparable decisions. Each scenario states context fit and whether cached input had to fall back to the published list-input rate.

Chat turn

1K fresh input + 500 output tokens

DeepSeek V3.1 (Reasoning)
Self-hosted; infrastructure cost varies
Fits in one request
Nemotron 3 Ultra
Self-hosted; infrastructure cost varies
Fits in one request

DeepSeek V3.1 (Reasoning) has no comparable published API token rate. Nemotron 3 Ultra has no comparable published API token rate.

Repository review

50K fresh input + 3K output tokens

DeepSeek V3.1 (Reasoning)
Self-hosted; infrastructure cost varies
Fits in one request
Nemotron 3 Ultra
Self-hosted; infrastructure cost varies
Fits in one request

DeepSeek V3.1 (Reasoning) has no comparable published API token rate. Nemotron 3 Ultra has no comparable published API token rate.

Cache-heavy agent loop

200K cached + 20K fresh input + 10K output tokens

DeepSeek V3.1 (Reasoning)
Self-hosted; infrastructure cost varies
Does not fit in one request
Cached-input rate unavailable
Nemotron 3 Ultra
Self-hosted; infrastructure cost varies
Fits in one request
Cached-input rate unavailable

DeepSeek V3.1 (Reasoning) does not fit this workload in one request. DeepSeek V3.1 (Reasoning) has no comparable published API token rate. Nemotron 3 Ultra has no comparable published API token rate.

Cached input falls back to the list input rate only where a cached rate is unpublished

Specification differences

Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.

Context window

Maximum documented context; output-token limits may be lower.

DeepSeek V3.1 (Reasoning)

128K

Nemotron 3 Ultra

1M

API model ID

DeepSeek V3.1 (Reasoning)

Not sourced

Nemotron 3 Ultra

Not sourced

Cached-input rate

A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.

DeepSeek V3.1 (Reasoning)

No comparable hosted API rate

Nemotron 3 Ultra

No comparable hosted API rate

Documented inputs

DeepSeek V3.1 (Reasoning)

Not sourced

Nemotron 3 Ultra

Not sourced

Documented outputs

DeepSeek V3.1 (Reasoning)

Not sourced

Nemotron 3 Ultra

Not sourced

Provider availability

DeepSeek V3.1 (Reasoning)

Not sourced

Nemotron 3 Ultra

Not sourced

Reasoning profile

DeepSeek V3.1 (Reasoning)

Reasoning

Nemotron 3 Ultra

Reasoning

Weight access

DeepSeek V3.1 (Reasoning)

Open Weight

Nemotron 3 Ultra

Open Weight

License

DeepSeek V3.1 (Reasoning)

Open Weight

Nemotron 3 Ultra

Open Weight

Release date

DeepSeek V3.1 (Reasoning)

2025-08-21

Nemotron 3 Ultra

2026-06-04

If you already use one of these models

Deployment change
The models list different providers, so authentication, endpoint behavior, limits, and feature support may change.
Quality signal
Nemotron 3 Ultra has the higher public point estimate, 47.25 versus 39.24. Their conditional score ranges overlap. These ranges do not establish rank confidence.
Workload cost
A complete comparable API-rate estimate is not available for both models.
Context tradeoff
Nemotron 3 Ultra has the larger documented window (1M).
Run the same representative tasks against both endpoints before changing production traffic.

Questions

Which is better, DeepSeek V3.1 (Reasoning) or Nemotron 3 Ultra?

Nemotron 3 Ultra has the higher public point estimate, 47.25 versus 39.24. Their conditional score ranges overlap. These ranges do not establish rank confidence. The page therefore keeps the decision tied to the specific documented workload.

Which is better for coding, DeepSeek V3.1 (Reasoning) or Nemotron 3 Ultra?

DeepSeek V3.1 (Reasoning) is not ranked on the public lane for coding, so no winner is named for coding.

Which is better for agentic tasks, DeepSeek V3.1 (Reasoning) or Nemotron 3 Ultra?

DeepSeek V3.1 (Reasoning) is not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.

Which costs less, DeepSeek V3.1 (Reasoning) or Nemotron 3 Ultra?

Both models do not have comparable published API token rates, so this page does not name a universal price winner.

Which has the larger context window, DeepSeek V3.1 (Reasoning) or Nemotron 3 Ultra?

Nemotron 3 Ultra has the larger documented context window: 1M, compared with 128K.

Benchmark evidence

The full public result ledger is available for audit without forcing a wide desktop table onto a phone.

Browse raw public benchmark evidence27 rows

Agentic

  • Terminal-Bench 2.1

    DeepSeek V3.1 (Reasoning)—
    Nemotron 3 Ultra56.4%
    Source

    Not directly comparable

  • PinchBench

    DeepSeek V3.1 (Reasoning)—
    Nemotron 3 Ultra90.0%
    Source

    Not directly comparable

  • BrowseComp

    DeepSeek V3.1 (Reasoning)—
    Nemotron 3 Ultra44.4%
    Source

    Not directly comparable

  • τ³-bench results

    DeepSeek V3.1 (Reasoning)—
    Nemotron 3 Ultra70.9%
    Source

    Not directly comparable

  • HLE w/ tools

    DeepSeek V3.1 (Reasoning)—
    Nemotron 3 Ultra37.4%
    Source

    Not directly comparable

  • Terminal-Bench 2.1 (Vals)

    DeepSeek V3.1 (Reasoning)—
    Nemotron 3 Ultra50.9%
    Source

    Not directly comparable

Coding

  • LiveCodeBench

    DeepSeek V3.1 (Reasoning)74.8%
    Source
    Nemotron 3 Ultra—

    Not directly comparable

  • SWE-bench Verified

    DeepSeek V3.1 (Reasoning)—
    Nemotron 3 Ultra71.9%
    Source

    Not directly comparable

  • SWE Multilingual

    DeepSeek V3.1 (Reasoning)—
    Nemotron 3 Ultra67.7%
    Source

    Not directly comparable

  • LiveCodeBench v6

    DeepSeek V3.1 (Reasoning)—
    Nemotron 3 Ultra89.0%
    Source

    Not directly comparable

  • SciCode

    DeepSeek V3.1 (Reasoning)—
    Nemotron 3 Ultra44.6%
    Source

    Not directly comparable

  • Terminal-Bench 2.1

    DeepSeek V3.1 (Reasoning)—
    Nemotron 3 Ultra56.4%
    Source

    Not directly comparable

  • LiveCodeBench (Vals)

    DeepSeek V3.1 (Reasoning)—
    Nemotron 3 Ultra86.0%
    Source

    Not directly comparable

  • SWE-bench (Vals)

    DeepSeek V3.1 (Reasoning)—
    Nemotron 3 Ultra69.0%
    Source

    Not directly comparable

Reasoning

  • CritPt

    DeepSeek V3.1 (Reasoning)—
    Nemotron 3 Ultra3.1%
    Source

    Not directly comparable

  • LongBench v2

    DeepSeek V3.1 (Reasoning)—
    Nemotron 3 Ultra61.9%
    Source

    Not directly comparable

Knowledge

  • GPQA

    DeepSeek V3.1 (Reasoning)80.1%
    Source
    Nemotron 3 Ultra87%
    Source

    Nemotron 3 Ultra leads this result

  • MMLU-Pro

    DeepSeek V3.1 (Reasoning)84.8%
    Source
    Nemotron 3 Ultra86.8%
    Source

    Nemotron 3 Ultra leads this result

  • HLE

    DeepSeek V3.1 (Reasoning)15.9%
    Source
    Nemotron 3 Ultra26.7%
    Source

    Nemotron 3 Ultra leads this result

  • GPQA-D

    DeepSeek V3.1 (Reasoning)—
    Nemotron 3 Ultra87.0%
    Source

    Not directly comparable

  • HLE w/o tools

    DeepSeek V3.1 (Reasoning)—
    Nemotron 3 Ultra26.7%
    Source

    Not directly comparable

  • GPQA Diamond (Vals)

    DeepSeek V3.1 (Reasoning)—
    Nemotron 3 Ultra86.1%
    Source

    Not directly comparable

  • MMLU-Pro (Vals)

    DeepSeek V3.1 (Reasoning)—
    Nemotron 3 Ultra85.8%
    Source

    Not directly comparable

Multilingual

  • MMLU-ProX

    DeepSeek V3.1 (Reasoning)—
    Nemotron 3 Ultra83%
    Source

    Not directly comparable

Instruction following

  • IFBench

    DeepSeek V3.1 (Reasoning)—
    Nemotron 3 Ultra81.7%
    Source

    Not directly comparable

Math

  • AIME 2024

    DeepSeek V3.1 (Reasoning)93.1%
    Source
    Nemotron 3 Ultra—

    Not directly comparable

  • AIME 2025

    DeepSeek V3.1 (Reasoning)88.4%
    Source
    Nemotron 3 Ultra—

    Not directly comparable

27 public results · 3 shared

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Last updated October 14, 2026