Pairwise benchmark snapshot · Aug 17, 2026

GPT-5 mini vs Kimi Chat 1.5 benchmark

Name: GPT-5 mini vs Kimi Chat 1.5 AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

This page compares GPT-5 mini (OpenAI) and Kimi Chat 1.5 (Moonshot) using the latest snapshots we have as of Aug 17, 2026. On preference Elo, Kimi Chat 1.5 is ahead by 10 points (1,420 vs 1,410; lmarena (Aug 17, 2026)). On SWE-bench coding, GPT-5 mini resolves 52.4% versus 51% (swebench (Aug 17, 2026)). GPT-5 mini streams faster (155 tok/s) while Kimi Chat 1.5 is the cheaper output token ($0.8/1M). Kimi Chat 1.5 has the larger context window (2M tokens). Every cell below is a dated snapshot from a named public source — we do not invent missing scores, and we do not run SWE-bench ourselves.

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OpenAI

GPT-5 mini

Cost-efficient GPT-5 distill for high-volume agents.

Elo 1,410$2/1M out

Moonshot

Kimi Chat 1.5

Moonshot ultra-long context model supporting up to 2 million tokens per request.

Elo 1,420$0.8/1M out

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Model A

Model B

Quick vs:vs Claude Opus 4.5 vs Claude Opus 4.6 vs Claude Sonnet 4.5 vs Claude 3.7 Sonnet

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

GPT-5 mini (6)vsKimi Chat 1.5 (4)

GPT-5 mini: 6W (60%)Overall: GPT-5 miniKimi Chat 1.5: 4W (40%)

← GPT-5 miniKimi Chat 1.5 →

GPT-5 mini (4/5)

Intelligence & Reasoning

Preference Elo, Coding proficiency, SWE-bench & LiveBench accuracy

Preference Elo

1,410vs1,420

Coding Elo

1,395vs1,390

SWE-bench

52.4%vs51%

LiveBench

61.2%vs58%

GPQA Diamond

72%vs71.5%

GPT-5 mini: 4WKimi Chat 1.5: 1W

GPT-5 mini (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

155 tok/svs95 tok/s

Time to first token

140 msvs210 ms

GPT-5 mini: 2WKimi Chat 1.5: 0W

Kimi Chat 1.5 (3/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$2/1Mvs$0.8/1M

Input price

$0.25/1Mvs$0.2/1M

Context window

400kvs2M

GPT-5 mini: 0WKimi Chat 1.5: 3W

Capability Matchup Radar

Multi-Dimensional Capability Radar

Each spoke is a skill. Farther from the center is better (0–100th percentile). Tap any dot to inspect details.

Tap any node to inspect

Percentile 0–100

Dimensional AdvantageGPT-5 mini 4/6

Preference Elo

Kimi Chat 1.5

10 pts advantage

Throughput Speed

GPT-5 mini

60 tok/s faster

Price Efficiency

Kimi Chat 1.5

$1.20/1M cheaper

Full Benchmark Score Matrix

—

Elo

High is better

1,410

EloHigh is better

1,420+1%

Code Elo

High is better

1,395

Code EloHigh is better

1,390

LiveBench

High is better

+6%61.2%

LiveBenchHigh is better

58%

SWE-bench

High is better

+3%52.4%

SWE-benchHigh is better

51%

GPQA

High is better

+1%72%

GPQAHigh is better

71.5%

TTFT

Low is better

+50%140 ms

TTFTLow is better

210 ms

Speed

High is better

+63%155 tok/s

SpeedHigh is better

95 tok/s

In $

Low is better

$0.25/1M

In $Low is better

$0.2/1M+25%

Out $

Low is better

$2/1M

Out $Low is better

$0.8/1M+150%

Context

High is better

400k

ContextHigh is better

2M+400%

Interactive Simulator

Workload Cost & Savings Calculator

Simulate monthly production API costs based on published $/1M tokens.

Save up to 51% with Kimi Chat 1.5

Monthly Volume50M tokens/mo

Quick Presets:

Token Ratio (In vs Out)70% In / 30% Out

RAG / Search (10% out)Coding / Chat (50% out)

GPT-5 mini$38.75 / mo

In: $8.75Out: $30.00

Kimi Chat 1.5$19.00 / mo

In: $7.00Out: $12.00

Estimated Cost Delta

Kimi Chat 1.5 is estimated to save $19.75/month ($237/year).

Based on 50M tokens (30% gen)

Key Selection Recommendations

1
GPT-5 mini:Pick GPT-5 mini when repo-level coding accuracy is the constraint.
2
Kimi Chat 1.5:Pick Kimi Chat 1.5 when you are optimizing output cost.
3
GPT-5 mini:Pick GPT-5 mini when time-to-first-token matters more than peak Elo.

Recommended Workload Routing

Repo / coding agentsGPT-5 mini

Higher SWE-bench (52.4%).

High-volume chatKimi Chat 1.5

Lower output list price ($0.8/1M).

Voice / low-latency UIGPT-5 mini

Lower TTFT (140 ms).

Long-document RAGKimi Chat 1.5

Larger window (2M).

Screenshots / visionGPT-5 mini

GPT-5 mini is the side marked multimodal in the catalog.

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	GPT-5 mini	Higher SWE-bench (52.4%).
High-volume chat	Kimi Chat 1.5	Lower output list price ($0.8/1M).
Voice / low-latency UI	GPT-5 mini	Lower TTFT (140 ms).
Long-document RAG	Kimi Chat 1.5	Larger window (2M).
Screenshots / vision	GPT-5 mini	GPT-5 mini is the side marked multimodal in the catalog.

Related Editorial Dispatches & Benchmark Notes

View all news

launchAug 8, 2025

GPT-5 mini: the 2025 distill still useful as a cheap OpenAI baseline

High-volume agents that cannot pay Sol. Compare to Luna before you assume the new cheap SKU wins.

Community Sentiment

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LIVE

OpenAI

GPT-5 mini

Elo 1,410

LiveBench61.2%

SWE-bench52.4%

Speed155 tok/s

Output cost$2/1M

Moonshot

Kimi Chat 1.5

Elo 1,420

LiveBench58%

SWE-bench51%

Speed95 tok/s

Output cost$0.8/1M

Frequently Asked Questions

Which is better overall, GPT-5 mini or Kimi Chat 1.5?: Kimi Chat 1.5 has the higher preference Elo in our latest snapshot (1,420). “Better” still depends on coding, price, and latency — see the table.
Which is better at coding, GPT-5 mini or Kimi Chat 1.5?: GPT-5 mini leads SWE-bench at 52.4% vs 51%. SWE-bench is one harness, not your repo.
Which is cheaper to run in production?: Kimi Chat 1.5 output tokens are $0.8/1M versus $2/1M. Input prices and retry rates still move the real bill.
Which is faster, GPT-5 mini or Kimi Chat 1.5?: GPT-5 mini has the lower time-to-first-token (140 ms vs 210 ms). Tokens/sec is a separate column if you care about long completions.
Which has the larger context window?: Kimi Chat 1.5 accepts 2M tokens versus 400k.
Can I self-host either model?: Neither model is marked open-weights here. You are comparing hosted APIs.
Are these scores from CompareLLM’s own evals?: No. V1 aggregates public leaderboards (and optional first-party latency pings). Each cell names its source and date. Read /methodology.
What does preference Elo mean on this page?: Preference Elo is a crowd vote from LMArena / Arena. People see two hidden answers and pick the one they like more. The model that wins more often gets a higher Elo. That means people preferred it — not that it passed a school test. It is not SWE-bench, not accuracy, and not a number we invent. GPT-5 mini and Kimi Chat 1.5 Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Similar Head-to-Head Comparisons

All GPT-5 mini matchups →|All Kimi Chat 1.5 matchups →

GPT-5 mini vs OpenAI: o3 Mini (previous gpt-mini)GPT-5 mini vs GPT-5.6 Luna (next gpt-mini)Kimi Chat 1.5 vs MoonshotAI: Kimi K2 0711 (next kimi)Kimi K3 vs Kimi Chat 1.5 GPT-4.5 Orion vs Kimi Chat 1.5 GPT-5.6 Terra vs Kimi Chat 1.5

GPT-5 mini vs Kimi Chat 1.5 benchmark

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

GPT-5 mini (6)vsKimi Chat 1.5 (4)

GPT-5 mini: 6W (60%)Overall: GPT-5 miniKimi Chat 1.5: 4W (40%)

← GPT-5 miniKimi Chat 1.5 →

GPT-5 mini (4/5)

Intelligence & Reasoning

Preference Elo, Coding proficiency, SWE-bench & LiveBench accuracy

Preference Elo

1,410vs1,420

Coding Elo

1,395vs1,390

SWE-bench

52.4%vs51%

LiveBench

61.2%vs58%

GPQA Diamond

72%vs71.5%

GPT-5 mini: 4WKimi Chat 1.5: 1W

GPT-5 mini (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

155 tok/svs95 tok/s

Time to first token

140 msvs210 ms

GPT-5 mini: 2WKimi Chat 1.5: 0W

Kimi Chat 1.5 (3/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$2/1Mvs$0.8/1M

Input price

$0.25/1Mvs$0.2/1M

Context window

400kvs2M

GPT-5 mini: 0WKimi Chat 1.5: 3W

Recommended Workload Routing

Repo / coding agentsGPT-5 mini

Higher SWE-bench (52.4%).

High-volume chatKimi Chat 1.5

Lower output list price ($0.8/1M).

Voice / low-latency UIGPT-5 mini

Lower TTFT (140 ms).

Long-document RAGKimi Chat 1.5

Larger window (2M).

Screenshots / visionGPT-5 mini

GPT-5 mini is the side marked multimodal in the catalog.

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	GPT-5 mini	Higher SWE-bench (52.4%).
High-volume chat	Kimi Chat 1.5	Lower output list price ($0.8/1M).
Voice / low-latency UI	GPT-5 mini	Lower TTFT (140 ms).
Long-document RAG	Kimi Chat 1.5	Larger window (2M).
Screenshots / vision	GPT-5 mini	GPT-5 mini is the side marked multimodal in the catalog.

Frequently Asked Questions

Which is better overall, GPT-5 mini or Kimi Chat 1.5?

Kimi Chat 1.5 has the higher preference Elo in our latest snapshot (1,420). “Better” still depends on coding, price, and latency — see the table.

Which is better at coding, GPT-5 mini or Kimi Chat 1.5?

GPT-5 mini leads SWE-bench at 52.4% vs 51%. SWE-bench is one harness, not your repo.

Which is cheaper to run in production?

Kimi Chat 1.5 output tokens are $0.8/1M versus $2/1M. Input prices and retry rates still move the real bill.

Which is faster, GPT-5 mini or Kimi Chat 1.5?

GPT-5 mini has the lower time-to-first-token (140 ms vs 210 ms). Tokens/sec is a separate column if you care about long completions.

Which has the larger context window?

Kimi Chat 1.5 accepts 2M tokens versus 400k.

Can I self-host either model?

Neither model is marked open-weights here. You are comparing hosted APIs.

Are these scores from CompareLLM’s own evals?

No. V1 aggregates public leaderboards (and optional first-party latency pings). Each cell names its source and date. Read /methodology.

What does preference Elo mean on this page?

Preference Elo is a crowd vote from LMArena / Arena. People see two hidden answers and pick the one they like more. The model that wins more often gets a higher Elo. That means people preferred it — not that it passed a school test. It is not SWE-bench, not accuracy, and not a number we invent. GPT-5 mini and Kimi Chat 1.5 Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

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Interactive Comparison Diagram

Tug-of-War Matchup Matrix

Intelligence & Reasoning

Speed & Latency

Pricing & Capacity

Multi-Dimensional Capability Radar

Kimi Chat 1.5

GPT-5 mini

Kimi Chat 1.5

Full Benchmark Score Matrix

Workload Cost & Savings Calculator

Key Selection Recommendations

Recommended Workload Routing

Related Editorial Dispatches & Benchmark Notes

GPT-5 mini: the 2025 distill still useful as a cheap OpenAI baseline

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Community Discussions (0)

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CompareLLM Matrix

GPT-5 mini

Kimi Chat 1.5

Frequently Asked Questions

Related news

Similar Head-to-Head Comparisons

Swap or Add Any Model to this Matchup

Interactive Comparison Diagram

Tug-of-War Matchup Matrix

Intelligence & Reasoning

Speed & Latency

Pricing & Capacity

Multi-Dimensional Capability Radar

Kimi Chat 1.5

GPT-5 mini

Kimi Chat 1.5

Full Benchmark Score Matrix

Workload Cost & Savings Calculator

Key Selection Recommendations

Recommended Workload Routing

Related Editorial Dispatches & Benchmark Notes

GPT-5 mini: the 2025 distill still useful as a cheap OpenAI baseline

Cast Your Matchup Vote

Community Discussions (0)

Share card

CompareLLM Matrix

GPT-5 mini

Kimi Chat 1.5

Frequently Asked Questions

Related news

Similar Head-to-Head Comparisons