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Model comparison

Pokee-Isaac 28B vs Qwen3.6 Plus

Updated August 4, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.

Pokee-Isaac 28B

Pokee AI

—

Evidence status unavailable

90% interval unavailable

Qwen3.6 Plus

Alibaba

64.6/100

Supported · Public rank #34

90% interval 55.9–73.3

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

1 results are shared. Category rows based on different benchmark sets are marked directional and do not name a winner.

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

    No shared weighted benchmark basis supports a winner.

    Confidence: limited

  • Agentic work

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

    Not enough matched evidence

    No shared weighted benchmark basis supports a winner.

    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

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
1
Pokee-Isaac 28B only
6
Qwen3.6 Plus only
42
Like-for-like categories
0 / 8

Category results, on a stated basis

Each row states whether both averages use the same weighted benchmark set. Directional and not-comparable rows remain visible, but they never receive a winner in this template.

Agentic

Not comparable
Pokee-Isaac 28B
Not measured
Qwen3.6 Plus
61.6
Weighted basis
0 vs 1 rows
Reading
Not comparable

Coding

Not comparable
Pokee-Isaac 28B
Not measured
Qwen3.6 Plus
70.3
Weighted basis
0 vs 2 rows
Reading
Not comparable

Reasoning

Not comparable
Pokee-Isaac 28B
60.7
Qwen3.6 Plus
62.0
Weighted basis
1 vs 1 rows
Reading
Not comparable

Knowledge

Not comparable
Pokee-Isaac 28B
Not measured
Qwen3.6 Plus
57.1
Weighted basis
0 vs 4 rows
Reading
Not comparable

Math

Not comparable
Pokee-Isaac 28B
Not measured
Qwen3.6 Plus
60.5
Weighted basis
0 vs 4 rows
Reading
Not comparable

Multilingual

Not comparable
Pokee-Isaac 28B
Not measured
Qwen3.6 Plus
84.7
Weighted basis
0 vs 1 rows
Reading
Not comparable

Multimodal

Not comparable
Pokee-Isaac 28B
Not measured
Qwen3.6 Plus
79.8
Weighted basis
0 vs 2 rows
Reading
Not comparable

Instruction following

Not comparable
Pokee-Isaac 28B
Not measured
Qwen3.6 Plus
82.3
Weighted basis
0 vs 2 rows
Reading
Not comparable

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

Pokee-Isaac 28B
$0.00065
Fits in one request
Qwen3.6 Plus
API rate not published
Fits in one request

Qwen3.6 Plus has no comparable published API token rate.

Repository review

50K fresh input + 3K output tokens

Pokee-Isaac 28B
$0.0105
Fits in one request
Qwen3.6 Plus
API rate not published
Fits in one request

Qwen3.6 Plus has no comparable published API token rate.

Cache-heavy agent loop

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

Pokee-Isaac 28B
$0.043
Fits in one request
Cached input priced at the published list-input rate
Qwen3.6 Plus
API rate not published
Fits in one request
Cached-input rate unavailable

Pokee-Isaac 28B has no published cached-input rate, so cached tokens use its listed input rate. Qwen3.6 Plus 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.

Pokee-Isaac 28B

10M

Pokee-Isaac 28B model page

Qwen3.6 Plus

1M

Cached-input rate

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

Pokee-Isaac 28B

Not published

Pokee-Isaac 28B model page

Qwen3.6 Plus

No comparable hosted API rate

Documented inputs

Pokee-Isaac 28B

Not sourced

Qwen3.6 Plus

Not sourced

Documented outputs

Pokee-Isaac 28B

Not sourced

Qwen3.6 Plus

Not sourced

Provider availability

Pokee-Isaac 28B

Not sourced

Qwen3.6 Plus

Not sourced

Reasoning profile

Pokee-Isaac 28B

Reasoning

Qwen3.6 Plus

Reasoning

Weight access

Pokee-Isaac 28B

Proprietary

Qwen3.6 Plus

Proprietary

License

Pokee-Isaac 28B

Proprietary

Qwen3.6 Plus

Proprietary

Release date

Pokee-Isaac 28B

2026-08-03

Qwen3.6 Plus

2026-04-02

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 evidence49 rows

Agentic

  • Terminal-Bench 2.1

    Pokee-Isaac 28B65.1%
    Source
    Qwen3.6 Plus—

    Not directly comparable

  • BFCL v4

    Pokee-Isaac 28B70.9%
    Source
    Qwen3.6 Plus—

    Not directly comparable

  • τ³-bench results

    Pokee-Isaac 28B66.2%
    Source
    Qwen3.6 Plus70.7%
    Source

    Qwen3.6 Plus leads this result

  • MCP-Atlas claim coverage

    Pokee-Isaac 28B74.6%
    Source
    Qwen3.6 Plus—

    Not directly comparable

  • PinchBench

    Pokee-Isaac 28B95.7%
    Source
    Qwen3.6 Plus—

    Not directly comparable

  • Terminal-Bench 2.0

    Pokee-Isaac 28B—
    Qwen3.6 Plus61.6%
    Source

    Not directly comparable

  • Claw-Eval

    Pokee-Isaac 28B—
    Qwen3.6 Plus58.8%
    Source

    Not directly comparable

  • QwenClawBench

    Pokee-Isaac 28B—
    Qwen3.6 Plus57.2%
    Source

    Not directly comparable

  • VITA-Bench

    Pokee-Isaac 28B—
    Qwen3.6 Plus44.3%
    Source

    Not directly comparable

  • DeepPlanning

    Pokee-Isaac 28B—
    Qwen3.6 Plus41.5%
    Source

    Not directly comparable

  • Toolathlon

    Pokee-Isaac 28B—
    Qwen3.6 Plus39.8%
    Source

    Not directly comparable

  • MCP Atlas

    Pokee-Isaac 28B—
    Qwen3.6 Plus48.2%
    Source

    Not directly comparable

  • MCP-Tasks

    Pokee-Isaac 28B—
    Qwen3.6 Plus74.1%
    Source

    Not directly comparable

  • WideResearch

    Pokee-Isaac 28B—
    Qwen3.6 Plus74.3%
    Source

    Not directly comparable

  • Gert Labs

    Pokee-Isaac 28B—
    Qwen3.6 Plus50.60%
    Source

    Not directly comparable

  • ResearchClawBench

    Pokee-Isaac 28B—
    Qwen3.6 Plus18.0%
    Source

    Not directly comparable

Coding

  • Terminal-Bench 2.1

    Pokee-Isaac 28B65.1%
    Source
    Qwen3.6 Plus—

    Not directly comparable

  • SWE-bench Verified

    Pokee-Isaac 28B—
    Qwen3.6 Plus78.8%
    Source

    Not directly comparable

  • SWE-bench Pro

    Pokee-Isaac 28B—
    Qwen3.6 Plus56.6%
    Source

    Not directly comparable

  • SWE Multilingual

    Pokee-Isaac 28B—
    Qwen3.6 Plus73.8%
    Source

    Not directly comparable

  • LiveCodeBench v6

    Pokee-Isaac 28B—
    Qwen3.6 Plus87.1%
    Source

    Not directly comparable

  • Vibe Code Bench

    Pokee-Isaac 28B—
    Qwen3.6 Plus25.56%
    Source

    Not directly comparable

Reasoning

  • MRCRv2

    Pokee-Isaac 28B60.7%
    Source
    Qwen3.6 Plus—

    Not directly comparable

  • AI-Needle

    Pokee-Isaac 28B—
    Qwen3.6 Plus68.3%
    Source

    Not directly comparable

  • LongBench v2

    Pokee-Isaac 28B—
    Qwen3.6 Plus62%
    Source

    Not directly comparable

Knowledge

  • GPQA

    Pokee-Isaac 28B—
    Qwen3.6 Plus90.4%
    Source

    Not directly comparable

  • SuperGPQA

    Pokee-Isaac 28B—
    Qwen3.6 Plus71.6%
    Source

    Not directly comparable

  • MMLU-Pro

    Pokee-Isaac 28B—
    Qwen3.6 Plus88.5%
    Source

    Not directly comparable

  • MMLU-Redux

    Pokee-Isaac 28B—
    Qwen3.6 Plus94.5%
    Source

    Not directly comparable

  • C-Eval

    Pokee-Isaac 28B—
    Qwen3.6 Plus93.3%
    Source

    Not directly comparable

  • HLE

    Pokee-Isaac 28B—
    Qwen3.6 Plus28.8%
    Source

    Not directly comparable

Math

  • AIME26

    Pokee-Isaac 28B—
    Qwen3.6 Plus95.3%
    Source

    Not directly comparable

  • HMMT Feb 2025

    Pokee-Isaac 28B—
    Qwen3.6 Plus96.7%
    Source

    Not directly comparable

  • HMMT Nov 2025

    Pokee-Isaac 28B—
    Qwen3.6 Plus94.6%
    Source

    Not directly comparable

  • HMMT Feb 2026

    Pokee-Isaac 28B—
    Qwen3.6 Plus87.8%
    Source

    Not directly comparable

  • MMAnswerBench

    Pokee-Isaac 28B—
    Qwen3.6 Plus83.8%
    Source

    Not directly comparable

  • FrontierMath v2 (Tiers 1-3)

    Pokee-Isaac 28B—
    Qwen3.6 Plus26.207%
    Source

    Not directly comparable

  • FrontierMath v2 (Tier 4)

    Pokee-Isaac 28B—
    Qwen3.6 Plus8.333%
    Source

    Not directly comparable

Multilingual

  • MMLU-ProX

    Pokee-Isaac 28B—
    Qwen3.6 Plus84.7%
    Source

    Not directly comparable

  • NOVA-63

    Pokee-Isaac 28B—
    Qwen3.6 Plus57.9%
    Source

    Not directly comparable

Multimodal

  • MMMU

    Pokee-Isaac 28B—
    Qwen3.6 Plus86.0%
    Source

    Not directly comparable

  • MMMU-Pro

    Pokee-Isaac 28B—
    Qwen3.6 Plus78.8%
    Source

    Not directly comparable

  • MathVision

    Pokee-Isaac 28B—
    Qwen3.6 Plus88.0%
    Source

    Not directly comparable

  • VideoMMMU

    Pokee-Isaac 28B—
    Qwen3.6 Plus84.0%
    Source

    Not directly comparable

  • ScreenSpot Pro

    Pokee-Isaac 28B—
    Qwen3.6 Plus68.2%
    Source

    Not directly comparable

  • CharXiv

    Pokee-Isaac 28B—
    Qwen3.6 Plus81.5%
    Source

    Not directly comparable

  • V*

    Pokee-Isaac 28B—
    Qwen3.6 Plus96.9%
    Source

    Not directly comparable

Instruction following

  • IFEval

    Pokee-Isaac 28B—
    Qwen3.6 Plus94.3%
    Source

    Not directly comparable

  • IFBench

    Pokee-Isaac 28B—
    Qwen3.6 Plus75.8%
    Source

    Not directly comparable

Frequently asked questions

Which is better, Pokee-Isaac 28B or Qwen3.6 Plus?

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, Pokee-Isaac 28B or Qwen3.6 Plus?

The published evidence does not provide a shared weighted coding basis for both models, so BenchLM does not name a coding winner.

Which is better for agentic tasks, Pokee-Isaac 28B or Qwen3.6 Plus?

The published evidence does not provide a shared weighted agentic tasks basis for both models, so BenchLM does not name a agentic tasks winner.

Which costs less, Pokee-Isaac 28B or Qwen3.6 Plus?

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, Pokee-Isaac 28B or Qwen3.6 Plus?

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

Related comparisons

Compare API pricing Read the methodology Open the model selector

Last updated August 4, 2026

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