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GPT Realtime 2.1 Mini vs Kimi K2.5

Updated October 25, 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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Decision reading

The public evidence has no benchmark result shared by both models, so it does not support a quality verdict. Use the documented cost, context, and runtime rows instead. 0 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.

Model A
OpenAI logo

OpenAI

—

Evidence status unavailable

90% interval unavailable

Model B
Moonshot AI logo

Moonshot AI

53.12/100

Supported · Public rank #82

90% interval 44.5–61.8

Shared results
0
GPT Realtime 2.1 Mini only
0
Kimi K2.5 only
68
Like-for-like categories
0 / 8
Supported: Kimi K2.5How 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

    Kimi K2.5

    Kimi K2.5 has the larger documented context window.

    Confidence: documented
  • Chat turn cost

    1K fresh input + 500 output tokens

    GPT Realtime 2.1 Mini

    GPT Realtime 2.1 Mini has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.

    Confidence: listed-rates
Show secondary and unsupported calls
  • Repository review cost

    50K fresh input + 3K output tokens

    GPT Realtime 2.1 Mini

    GPT Realtime 2.1 Mini has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.

    Confidence: listed-rates
  • Coding work

    Code generation, repair, and software-engineering tasks

    Not enough matched evidence

    GPT Realtime 2.1 Mini 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

    GPT Realtime 2.1 Mini is not ranked on the public lane for agentic, so no winner is named for agentic.

    Confidence: limited
  • 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. GPT Realtime 2.1 Mini does not fit this workload in one request. Kimi K2.5 has no published cached-input rate, so cached tokens use its listed input rate.

    Confidence: rate-fallback

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.

—GPT Realtime 2.1 Mini38.8Kimi K2.5

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.

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.

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.

Agentic

Not comparable
GPT Realtime 2.1 Mini
Not ranked
Kimi K2.5
41.0
Estimated · #68/132
Basis
BenchAlign v5.8 lane · 0 vs 16 public rows
Reading
Not comparable

Coding

Not comparable
GPT Realtime 2.1 Mini
Not ranked
Kimi K2.5
38.8
Estimated · #70/153
Basis
BenchAlign v5.8 lane · 0 vs 10 public rows
Reading
Not comparable

Reasoning

Not comparable
GPT Realtime 2.1 Mini
Not ranked
Kimi K2.5
71.3
Unranked · 3 rankable rows
Basis
Provisional lane · 0 vs 1 weighted rows
Reading
Not comparable

Multimodal

Not comparable
GPT Realtime 2.1 Mini
Not ranked
Kimi K2.5
70.6
#34/56
Basis
Provisional lane · 0 vs 2 weighted rows
Reading
Not comparable

Knowledge

Not comparable
GPT Realtime 2.1 Mini
Not ranked
Kimi K2.5
50.9
Estimated · #77/187
Basis
BenchAlign v5.8 lane · 0 vs 8 public rows
Reading
Not comparable

Multilingual

Not comparable
GPT Realtime 2.1 Mini
Not ranked
Kimi K2.5
87.3
#8/17
Basis
Provisional lane · 0 vs 1 weighted rows
Reading
Not comparable

Instruction following

Not comparable
GPT Realtime 2.1 Mini
Not ranked
Kimi K2.5
85.8
#50/153
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Math

Not comparable
GPT Realtime 2.1 Mini
Not ranked
Kimi K2.5
83.3
Unranked · 7 rankable rows
Basis
Provisional lane · 0 vs 2 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.

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

GPT Realtime 2.1 Mini
$0.0018
Fits in one request
Kimi K2.5
$0.0021
Fits in one request

GPT Realtime 2.1 Mini has the lower modeled cost

Costs use the listed standard API rates.

Repository review

50K fresh input + 3K output tokens

GPT Realtime 2.1 Mini
$0.0372
Fits in one request
Kimi K2.5
$0.039
Fits in one request

GPT Realtime 2.1 Mini has the lower modeled cost

Costs use the listed standard API rates.

Cache-heavy agent loop

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

GPT Realtime 2.1 Mini
$0.048
Does not fit in one request
Kimi K2.5
$0.162
Fits in one request
Cached input priced at the published list-input rate

GPT Realtime 2.1 Mini does not fit this workload in one request. Kimi K2.5 has no published cached-input rate, so cached tokens use its listed input 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.

Cached-input rate

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

GPT Realtime 2.1 Mini

$0.06 per 1M cached input tokens

OpenAI model documentation

Kimi K2.5

Not published

Reasoning profile

GPT Realtime 2.1 Mini

Non-Reasoning

Kimi K2.5

Non-Reasoning

Weight access

GPT Realtime 2.1 Mini

Proprietary

Kimi K2.5

Open Weight

License

GPT Realtime 2.1 Mini

Proprietary

Kimi K2.5

Open Weight

Release date

GPT Realtime 2.1 Mini

2026-07-06

Kimi K2.5

2026-01-27

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
The public evidence has no benchmark result shared by both models, so it does not support a quality verdict.
Workload cost
Repository review: $0.0372 vs $0.039. Cache-heavy agent loop: $0.048 vs $0.162.
Context tradeoff
Kimi K2.5 has the larger documented window (256K).
Run the same representative tasks against both endpoints before changing production traffic.

Questions

Which is better, GPT Realtime 2.1 Mini or Kimi K2.5?

The public evidence has no benchmark result shared by both models, so it does not support a quality verdict. The page therefore keeps the decision tied to the specific documented workload.

Which is better for coding, GPT Realtime 2.1 Mini or Kimi K2.5?

GPT Realtime 2.1 Mini is not ranked on the public lane for coding, so no winner is named for coding.

Which is better for agentic tasks, GPT Realtime 2.1 Mini or Kimi K2.5?

GPT Realtime 2.1 Mini is not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.

Which costs less, GPT Realtime 2.1 Mini or Kimi K2.5?

For the stated presets, chat costs $0.0018 on GPT Realtime 2.1 Mini and $0.0021 on Kimi K2.5; repository review costs $0.0372 and $0.039; the cache-heavy agent loop costs $0.048 and $0.162. GPT Realtime 2.1 Mini does not fit this workload in one request. Kimi K2.5 has no published cached-input rate, so cached tokens use its listed input rate.

Which has the larger context window, GPT Realtime 2.1 Mini or Kimi K2.5?

Kimi K2.5 has the larger documented context window: 256K, compared with 128K.

Self-host vs API cost

Estimates at 50,000 req/day · 1000 tokens/req average.

GPT Realtime 2.1 Mini
API / mo$2,250
Self-host / moNot listed
Break-even—
Proprietary model — self-hosting not applicable.
Kimi K2.5
API / mo$2,700
Self-host / mo$7,358
Break-even186M/day
Model the full break-even

Benchmark evidence

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

Browse raw public benchmark evidence68 rows

Agentic

  • Terminal-Bench 2.0

    GPT Realtime 2.1 Mini—
    Kimi K2.550.8%
    Source

    Not directly comparable

  • BrowseComp

    GPT Realtime 2.1 Mini—
    Kimi K2.560.6%
    Source

    Not directly comparable

  • OSWorld-Verified

    GPT Realtime 2.1 Mini—
    Kimi K2.563.3%
    Source

    Not directly comparable

  • Claw-Eval

    GPT Realtime 2.1 Mini—
    Kimi K2.552.3%
    Source

    Not directly comparable

  • QwenClawBench

    GPT Realtime 2.1 Mini—
    Kimi K2.554.3%
    Source

    Not directly comparable

  • τ³-bench results

    GPT Realtime 2.1 Mini—
    Kimi K2.565.7%
    Source

    Not directly comparable

  • DeepSearchQA

    GPT Realtime 2.1 Mini—
    Kimi K2.577.1%
    Source

    Not directly comparable

  • DeepPlanning

    GPT Realtime 2.1 Mini—
    Kimi K2.514.4%
    Source

    Not directly comparable

  • Toolathlon

    GPT Realtime 2.1 Mini—
    Kimi K2.527.8%
    Source

    Not directly comparable

  • MCP Atlas

    GPT Realtime 2.1 Mini—
    Kimi K2.529.5%
    Source

    Not directly comparable

  • MCP-Tasks

    GPT Realtime 2.1 Mini—
    Kimi K2.559.1%
    Source

    Not directly comparable

  • WideResearch

    GPT Realtime 2.1 Mini—
    Kimi K2.572.7%
    Source

    Not directly comparable

  • BFCL v4

    GPT Realtime 2.1 Mini—
    Kimi K2.568.3%
    Source

    Not directly comparable

  • Gert Labs

    GPT Realtime 2.1 Mini—
    Kimi K2.545.88%
    Source

    Not directly comparable

  • ResearchClawBench

    GPT Realtime 2.1 Mini—
    Kimi K2.514.0%
    Source

    Not directly comparable

  • JobBench

    GPT Realtime 2.1 Mini—
    Kimi K2.58.7%
    Source

    Not directly comparable

Coding

  • SWE-bench Verified

    GPT Realtime 2.1 Mini—
    Kimi K2.576.8%
    Source

    Not directly comparable

  • SWE-bench Verified*

    GPT Realtime 2.1 Mini—
    Kimi K2.570.8%
    Source

    Not directly comparable

  • LiveCodeBench v6

    GPT Realtime 2.1 Mini—
    Kimi K2.585.0%
    Source

    Not directly comparable

  • SWE-bench Pro

    GPT Realtime 2.1 Mini—
    Kimi K2.550.7%
    Source

    Not directly comparable

  • SWE Multilingual

    GPT Realtime 2.1 Mini—
    Kimi K2.573%
    Source

    Not directly comparable

  • SWE-Rebench

    GPT Realtime 2.1 Mini—
    Kimi K2.558.5%
    Source

    Not directly comparable

  • React Native Evals

    GPT Realtime 2.1 Mini—
    Kimi K2.577.2%
    Source

    Not directly comparable

  • NL2Repo

    GPT Realtime 2.1 Mini—
    Kimi K2.532%
    Source

    Not directly comparable

  • SciCode

    GPT Realtime 2.1 Mini—
    Kimi K2.548.7%
    Source

    Not directly comparable

  • Terminal-Bench 2.0

    GPT Realtime 2.1 Mini—
    Kimi K2.550.8%
    Source

    Not directly comparable

Reasoning

  • LongBench v2

    GPT Realtime 2.1 Mini—
    Kimi K2.561%
    Source

    Not directly comparable

Multimodal

  • MMMU

    GPT Realtime 2.1 Mini—
    Kimi K2.584.3%
    Source

    Not directly comparable

  • MMMU-Pro

    GPT Realtime 2.1 Mini—
    Kimi K2.578.5%
    Source

    Not directly comparable

  • RealWorldQA

    GPT Realtime 2.1 Mini—
    Kimi K2.581.0%
    Source

    Not directly comparable

  • OmniDocBench 1.5

    GPT Realtime 2.1 Mini—
    Kimi K2.588.8%
    Source

    Not directly comparable

  • Video-MME

    GPT Realtime 2.1 Mini—
    Kimi K2.587.4%
    Source

    Not directly comparable

  • Video-MME (with subtitle)

    GPT Realtime 2.1 Mini—
    Kimi K2.587.4%
    Source

    Not directly comparable

  • Video-MME (w/o subtitle)

    GPT Realtime 2.1 Mini—
    Kimi K2.583.2%
    Source

    Not directly comparable

  • MathVision

    GPT Realtime 2.1 Mini—
    Kimi K2.584.2%
    Source

    Not directly comparable

  • We-Math

    GPT Realtime 2.1 Mini—
    Kimi K2.584.7%
    Source

    Not directly comparable

  • DynaMath

    GPT Realtime 2.1 Mini—
    Kimi K2.584.4%
    Source

    Not directly comparable

  • SimpleVQA

    GPT Realtime 2.1 Mini—
    Kimi K2.571.2%
    Source

    Not directly comparable

  • MMLongBench-Doc

    GPT Realtime 2.1 Mini—
    Kimi K2.558.5%
    Source

    Not directly comparable

  • CC-OCR

    GPT Realtime 2.1 Mini—
    Kimi K2.579.7%
    Source

    Not directly comparable

  • AI2D_TEST

    GPT Realtime 2.1 Mini—
    Kimi K2.590.8%
    Source

    Not directly comparable

  • CountBench

    GPT Realtime 2.1 Mini—
    Kimi K2.594.1%
    Source

    Not directly comparable

  • RefCOCO (avg)

    GPT Realtime 2.1 Mini—
    Kimi K2.587.8%
    Source

    Not directly comparable

  • MMVU

    GPT Realtime 2.1 Mini—
    Kimi K2.580.4%
    Source

    Not directly comparable

  • VideoMMMU

    GPT Realtime 2.1 Mini—
    Kimi K2.586.6%
    Source

    Not directly comparable

  • MLVU (M-Avg)

    GPT Realtime 2.1 Mini—
    Kimi K2.585.0%
    Source

    Not directly comparable

  • CharXiv

    GPT Realtime 2.1 Mini—
    Kimi K2.577.5%
    Source

    Not directly comparable

Knowledge

  • GPQA

    GPT Realtime 2.1 Mini—
    Kimi K2.587.6%
    Source

    Not directly comparable

  • GPQA-D

    GPT Realtime 2.1 Mini—
    Kimi K2.587.6%
    Source

    Not directly comparable

  • SuperGPQA

    GPT Realtime 2.1 Mini—
    Kimi K2.569.2%
    Source

    Not directly comparable

  • MMLU-Pro

    GPT Realtime 2.1 Mini—
    Kimi K2.587.1%
    Source

    Not directly comparable

  • MMLU-Pro (Arcee)

    GPT Realtime 2.1 Mini—
    Kimi K2.587.1%
    Source

    Not directly comparable

  • MMLU-Redux

    GPT Realtime 2.1 Mini—
    Kimi K2.594.5%
    Source

    Not directly comparable

  • C-Eval

    GPT Realtime 2.1 Mini—
    Kimi K2.594%
    Source

    Not directly comparable

  • HLE

    GPT Realtime 2.1 Mini—
    Kimi K2.530.1%
    Source

    Not directly comparable

Multilingual

  • MMLU-ProX

    GPT Realtime 2.1 Mini—
    Kimi K2.582.3%
    Source

    Not directly comparable

  • NOVA-63

    GPT Realtime 2.1 Mini—
    Kimi K2.556.0%
    Source

    Not directly comparable

  • INCLUDE

    GPT Realtime 2.1 Mini—
    Kimi K2.583.3%
    Source

    Not directly comparable

  • PolyMath

    GPT Realtime 2.1 Mini—
    Kimi K2.543.1%
    Source

    Not directly comparable

  • MAXIFE

    GPT Realtime 2.1 Mini—
    Kimi K2.572.8%
    Source

    Not directly comparable

Instruction following

  • IFEval

    GPT Realtime 2.1 Mini—
    Kimi K2.593.9%
    Source

    Not directly comparable

Math

  • AIME 2025

    GPT Realtime 2.1 Mini—
    Kimi K2.596.1%
    Source

    Not directly comparable

  • AIME26

    GPT Realtime 2.1 Mini—
    Kimi K2.595.8%
    Source

    Not directly comparable

  • AIME25 (Arcee)

    GPT Realtime 2.1 Mini—
    Kimi K2.596.3%
    Source

    Not directly comparable

  • HMMT Feb 2025

    GPT Realtime 2.1 Mini—
    Kimi K2.595.4%
    Source

    Not directly comparable

  • HMMT Nov 2025

    GPT Realtime 2.1 Mini—
    Kimi K2.591.1%
    Source

    Not directly comparable

  • HMMT Feb 2026

    GPT Realtime 2.1 Mini—
    Kimi K2.587.1%
    Source

    Not directly comparable

  • MMAnswerBench

    GPT Realtime 2.1 Mini—
    Kimi K2.581.8%
    Source

    Not directly comparable

68 public results · 0 shared

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Last updated October 25, 2026