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Nemotron 3 Ultra vs Pokee-Isaac 28B

Decision reading

At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner.

2 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.

NVIDIA logo
Model A
Nemotron 3 Ultra

NVIDIA

40.5/100

Estimated · Public rank #187

90% interval 30.650.4

Pokee AI logo
Model B
Pokee-Isaac 28B

Pokee AI

Evidence status unavailable

90% interval unavailable

Updated September 18, 2026. We do not rank this pair: at least one has no public score. Public scores include evidence status and uncertainty.

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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

    Pokee-Isaac 28B

    Pokee-Isaac 28B 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

    Pokee-Isaac 28B 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

    Pokee-Isaac 28B is scored on Estimated evidence for agentic, so the reading is directional rather than like-for-like.

    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

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

    Confidence: rate-fallback

  • 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.

26.6Nemotron 3 UltraPokee-Isaac 28B

Not comparable · BenchAlign

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.

What is actually comparable

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

Shared results
2
Nemotron 3 Ultra only
22
Pokee-Isaac 28B only
5
Like-for-like categories
0 / 8

1 category rests on Estimated evidence or different evidence sets. Those rows remain visible for coverage context but do not name a winner.

Category results, on a stated basis

Each row shows the public-lane category score for both models: the BenchAlign 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.

Agentic

Directional only
Nemotron 3 Ultra
26.9
Supported · #147/154
Pokee-Isaac 28B
49.6
Estimated · #62/154
Basis
BenchAlign lane · 6 vs 5 public rows
Reading
Directional only

Coding

Not comparable
Nemotron 3 Ultra
26.6
Supported · #149/154
Pokee-Isaac 28B
Not ranked
Basis
BenchAlign lane · 7 vs 1 public rows
Reading
Not comparable

Reasoning

Not comparable
Nemotron 3 Ultra
48.7
Unranked · 1 rankable row
Pokee-Isaac 28B
38.6
Unranked · 1 rankable row
Basis
Provisional lane · 1 vs 1 weighted rows
Reading
Not comparable

Knowledge

Not comparable
Nemotron 3 Ultra
44.8
Estimated · #113/184
Pokee-Isaac 28B
Not ranked
Basis
BenchAlign lane · 7 vs 0 public rows
Reading
Not comparable

Math

Not comparable
Nemotron 3 Ultra
Not ranked
Pokee-Isaac 28B
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Multilingual

Not comparable
Nemotron 3 Ultra
47.4
#7/12
Pokee-Isaac 28B
Not ranked
Basis
Provisional lane · 1 vs 0 weighted rows
Reading
Not comparable

Multimodal

Not comparable
Nemotron 3 Ultra
Not ranked
Pokee-Isaac 28B
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Instruction following

Not comparable
Nemotron 3 Ultra
88.1
#26/124
Pokee-Isaac 28B
Not ranked
Basis
Provisional lane · 1 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) differ from the provisional-lane categories. Unranked scores sit on the lane’s scale but never name a winner. Like-for-like rows within 0.5 points read as a practical tie.

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.

A shared-evidence shape is not available.

BenchLM does not draw a radar or infer missing axes when the matched evidence is too sparse.

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

Nemotron 3 Ultra
Self-hosted; infrastructure cost varies
Fits in one request
Pokee-Isaac 28B
$0.00065
Fits in one request

Nemotron 3 Ultra has no comparable published API token rate.

Repository review

50K fresh input + 3K output tokens

Nemotron 3 Ultra
Self-hosted; infrastructure cost varies
Fits in one request
Pokee-Isaac 28B
$0.0105
Fits in one request

Nemotron 3 Ultra has no comparable published API token rate.

Cache-heavy agent loop

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

Nemotron 3 Ultra
Self-hosted; infrastructure cost varies
Fits in one request
Cached-input rate unavailable
Pokee-Isaac 28B
$0.043
Fits in one request
Cached input priced at the published list-input rate

Pokee-Isaac 28B has no published cached-input rate, so cached tokens use its listed input rate. Nemotron 3 Ultra has no comparable published API token rate.

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.

Nemotron 3 Ultra

1M

Pokee-Isaac 28B

Cached-input rate

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

Nemotron 3 Ultra

No comparable hosted API rate

Pokee-Isaac 28B

Documented inputs

Nemotron 3 Ultra

Not sourced

Pokee-Isaac 28B

Not sourced

Documented outputs

Nemotron 3 Ultra

Not sourced

Pokee-Isaac 28B

Not sourced

Provider availability

Nemotron 3 Ultra

Not sourced

Pokee-Isaac 28B

Not sourced

Reasoning profile

Nemotron 3 Ultra

Reasoning

Pokee-Isaac 28B

Reasoning

Weight access

Nemotron 3 Ultra

Open Weight

Pokee-Isaac 28B

Proprietary

License

Nemotron 3 Ultra

Open Weight

Pokee-Isaac 28B

Proprietary

Release date

Nemotron 3 Ultra

2026-06-04

Pokee-Isaac 28B

2026-08-03

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
At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner.
Workload cost
A complete comparable API-rate estimate is not available for both models.
Context tradeoff
Pokee-Isaac 28B has the larger documented window (10M).

Run the same representative tasks against both endpoints before changing production traffic.

Benchmark evidence

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

Browse raw public benchmark evidence29 rows

Agentic

  • Terminal-Bench 2.0

    Nemotron 3 Ultra56.4%
    Source
    Pokee-Isaac 28B

    Not directly comparable

  • PinchBench

    Nemotron 3 Ultra90.0%
    Source
    Pokee-Isaac 28B95.7%
    Source

    Pokee-Isaac 28B leads this result

  • BrowseComp

    Nemotron 3 Ultra44.4%
    Source
    Pokee-Isaac 28B

    Not directly comparable

  • τ³-bench results

    Nemotron 3 Ultra70.9%
    Source
    Pokee-Isaac 28B66.2%
    Source

    Nemotron 3 Ultra leads this result

  • HLE w/ tools

    Nemotron 3 Ultra37.4%
    Source
    Pokee-Isaac 28B

    Not directly comparable

  • Terminal-Bench 2.1 (Vals)

    Nemotron 3 Ultra50.9%
    Source
    Pokee-Isaac 28B

    Not directly comparable

  • Terminal-Bench 2.1

    Nemotron 3 Ultra
    Pokee-Isaac 28B65.1%
    Source

    Not directly comparable

  • BFCL v4

    Nemotron 3 Ultra
    Pokee-Isaac 28B70.9%
    Source

    Not directly comparable

  • MCP-Atlas claim coverage

    Nemotron 3 Ultra
    Pokee-Isaac 28B74.6%
    Source

    Not directly comparable

Coding

  • SWE-bench Verified

    Nemotron 3 Ultra71.9%
    Source
    Pokee-Isaac 28B

    Not directly comparable

  • SWE Multilingual

    Nemotron 3 Ultra67.7%
    Source
    Pokee-Isaac 28B

    Not directly comparable

  • LiveCodeBench v6

    Nemotron 3 Ultra89.0%
    Source
    Pokee-Isaac 28B

    Not directly comparable

  • SciCode

    Nemotron 3 Ultra44.6%
    Source
    Pokee-Isaac 28B

    Not directly comparable

  • Terminal-Bench 2.0

    Nemotron 3 Ultra56.4%
    Source
    Pokee-Isaac 28B

    Not directly comparable

  • LiveCodeBench (Vals)

    Nemotron 3 Ultra86.0%
    Source
    Pokee-Isaac 28B

    Not directly comparable

  • SWE-bench (Vals)

    Nemotron 3 Ultra69.0%
    Source
    Pokee-Isaac 28B

    Not directly comparable

  • Terminal-Bench 2.1

    Nemotron 3 Ultra
    Pokee-Isaac 28B65.1%
    Source

    Not directly comparable

Reasoning

  • CritPt

    Nemotron 3 Ultra3.1%
    Source
    Pokee-Isaac 28B

    Not directly comparable

  • LongBench v2

    Nemotron 3 Ultra61.9%
    Source
    Pokee-Isaac 28B

    Not directly comparable

  • MRCRv2

    Nemotron 3 Ultra
    Pokee-Isaac 28B60.7%
    Source

    Not directly comparable

Knowledge

  • GPQA

    Nemotron 3 Ultra87%
    Source
    Pokee-Isaac 28B

    Not directly comparable

  • GPQA-D

    Nemotron 3 Ultra87.0%
    Source
    Pokee-Isaac 28B

    Not directly comparable

  • HLE

    Nemotron 3 Ultra26.7%
    Source
    Pokee-Isaac 28B

    Not directly comparable

  • HLE w/o tools

    Nemotron 3 Ultra26.7%
    Source
    Pokee-Isaac 28B

    Not directly comparable

  • MMLU-Pro

    Nemotron 3 Ultra86.8%
    Source
    Pokee-Isaac 28B

    Not directly comparable

  • GPQA Diamond (Vals)

    Nemotron 3 Ultra86.1%
    Source
    Pokee-Isaac 28B

    Not directly comparable

  • MMLU-Pro (Vals)

    Nemotron 3 Ultra85.8%
    Source
    Pokee-Isaac 28B

    Not directly comparable

Multilingual

  • MMLU-ProX

    Nemotron 3 Ultra83%
    Source
    Pokee-Isaac 28B

    Not directly comparable

Instruction following

  • IFBench

    Nemotron 3 Ultra81.7%
    Source
    Pokee-Isaac 28B

    Not directly comparable

Questions

Which is better, Nemotron 3 Ultra or Pokee-Isaac 28B?

At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner. The page therefore keeps the decision tied to the specific documented workload.

Which is better for coding, Nemotron 3 Ultra or Pokee-Isaac 28B?

Pokee-Isaac 28B is not ranked on the public lane for coding, so no winner is named for coding.

Which is better for agentic tasks, Nemotron 3 Ultra or Pokee-Isaac 28B?

Pokee-Isaac 28B scores higher for agentic tasks on the public lane, 49.6 to 26.9. Pokee-Isaac 28B is scored on Estimated evidence for agentic tasks, so the reading is directional rather than like-for-like. BenchLM does not name a winner for agentic tasks from a directional reading; read the shared benchmark rows directly and test the models on the same task set.

Which costs less, Nemotron 3 Ultra or Pokee-Isaac 28B?

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, Nemotron 3 Ultra or Pokee-Isaac 28B?

Pokee-Isaac 28B has the larger documented context window: 10M, compared with 1M.

Related comparisons

Last updated September 18, 2026

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