Pairwise benchmark snapshot · Aug 16, 2026

GPT-4o mini vs Kimi Chat 1.5 benchmark

Name: GPT-4o mini vs Kimi Chat 1.5 AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

This page compares GPT-4o mini (OpenAI) and Kimi Chat 1.5 (Moonshot) using the latest snapshots we have as of Aug 16, 2026. On preference Elo, Kimi Chat 1.5 is ahead by 148 points (1,420 vs 1,272; seed-bootstrap (Aug 1, 2026)). On SWE-bench coding, Kimi Chat 1.5 resolves 51% versus 41.2% (seed-bootstrap (Aug 1, 2026)). GPT-4o mini streams faster (160 tok/s) while GPT-4o mini is the cheaper output token ($0.6/1M). 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.

Share Analysis:

WhatsApp Telegram X / Post LinkedIn Reddit

OpenAI

GPT-4o mini

Legacy small OpenAI model. Useful as a cheap baseline.

Elo 1,272$0.6/1M 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

Swap or Add Any Model to this Matchup

Instant pairwise benchmark recalculation across 400+ LLMs

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-4o mini (4)vsKimi Chat 1.5 (6)

GPT-4o mini: 4W (40%)Overall: Kimi Chat 1.5Kimi Chat 1.5: 6W (60%)

← GPT-4o miniKimi Chat 1.5 →

Kimi Chat 1.5 (5/5)

Intelligence & Reasoning

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

Preference Elo

1,272vs1,420

Coding Elo

—vs1,390

SWE-bench

41.2%vs51%

LiveBench

48.1%vs58%

GPQA Diamond

60.1%vs71.5%

GPT-4o mini: 0WKimi Chat 1.5: 5W

GPT-4o mini (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

160 tok/svs95 tok/s

Time to first token

130 msvs210 ms

GPT-4o mini: 2WKimi Chat 1.5: 0W

GPT-4o mini (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$0.6/1Mvs$0.8/1M

Input price

$0.15/1Mvs$0.2/1M

Context window

128kvs2M

GPT-4o mini: 2WKimi Chat 1.5: 1W

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 AdvantageKimi Chat 1.5 4/6

Preference Elo

Kimi Chat 1.5

148 pts advantage

Throughput Speed

GPT-4o mini

65 tok/s faster

Price Efficiency

GPT-4o mini

$0.20/1M cheaper

Full Benchmark Score Matrix

—

Elo

High is better

1,272

EloHigh is better

1,420+12%

Code Elo

High is better

—

Code EloHigh is better

1,390

LiveBench

High is better

48.1%

LiveBenchHigh is better

58%+21%

SWE-bench

High is better

41.2%

SWE-benchHigh is better

51%+24%

GPQA

High is better

60.1%

GPQAHigh is better

71.5%+19%

TTFT

Low is better

+62%130 ms

TTFTLow is better

210 ms

Speed

High is better

+68%160 tok/s

SpeedHigh is better

95 tok/s

In $

Low is better

+33%$0.15/1M

In $Low is better

$0.2/1M

Out $

Low is better

+33%$0.6/1M

Out $Low is better

$0.8/1M

Context

High is better

128k

ContextHigh is better

2M+1463%

Interactive Simulator

Workload Cost & Savings Calculator

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

Save up to 25% with GPT-4o mini

Monthly Volume50M tokens/mo

Quick Presets:

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

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

GPT-4o mini$14.25 / mo

In: $5.25Out: $9.00

Kimi Chat 1.5$19.00 / mo

In: $7.00Out: $12.00

Estimated Cost Delta

GPT-4o mini is estimated to save $4.75/month ($57/year).

Based on 50M tokens (30% gen)

Key Selection Recommendations

1
Kimi Chat 1.5:Pick Kimi Chat 1.5 when repo-level coding accuracy is the constraint.
2
GPT-4o mini:Pick GPT-4o mini when you are optimizing output cost.
3
GPT-4o mini:Pick GPT-4o mini when time-to-first-token matters more than peak Elo.

Recommended Workload Routing

Repo / coding agentsKimi Chat 1.5

Higher SWE-bench (51%).

High-volume chatGPT-4o mini

Lower output list price ($0.6/1M).

Voice / low-latency UIGPT-4o mini

Lower TTFT (130 ms).

Long-document RAGKimi Chat 1.5

Larger window (2M).

Screenshots / visionGPT-4o mini

GPT-4o mini is the side marked multimodal in the catalog.

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	Kimi Chat 1.5	Higher SWE-bench (51%).
High-volume chat	GPT-4o mini	Lower output list price ($0.6/1M).
Voice / low-latency UI	GPT-4o mini	Lower TTFT (130 ms).
Long-document RAG	Kimi Chat 1.5	Larger window (2M).
Screenshots / vision	GPT-4o mini	GPT-4o mini is the side marked multimodal in the catalog.

Community Sentiment

Cast Your Matchup Vote

0 total votes

Community Discussions (0)

No comments posted on this matchup yet. Be the first to share an evaluation note!

Share card

The real PNG is generated at /compare/gpt-4o-mini-vs-kimi-1-5-long/opengraph-image for crawlers.

PNG

CompareLLM Matrix

Verified head-to-head card

LIVE

OpenAI

GPT-4o mini

Elo 1,272

LiveBench48.1%

SWE-bench41.2%

Speed160 tok/s

Output cost$0.6/1M

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-4o 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-4o mini or Kimi Chat 1.5?: Kimi Chat 1.5 leads SWE-bench at 51% vs 41.2%. SWE-bench is one harness, not your repo.
Which is cheaper to run in production?: GPT-4o mini output tokens are $0.6/1M versus $0.8/1M. Input prices and retry rates still move the real bill.
Which is faster, GPT-4o mini or Kimi Chat 1.5?: GPT-4o mini has the lower time-to-first-token (130 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 128k.
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-4o 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-4o mini matchups →|All Kimi Chat 1.5 matchups →

GPT-4o mini vs OpenAI o1-mini (next gpt-mini)Kimi Chat 1.5 vs MoonshotAI: Kimi K2 0711 (next kimi)GPT-5 vs Kimi Chat 1.5 Kimi K3 vs Kimi Chat 1.5 GPT-4.5 Orion vs Kimi Chat 1.5 GPT-5.6 Sol vs Kimi Chat 1.5

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

GPT-4o mini: 4W (40%)Overall: Kimi Chat 1.5Kimi Chat 1.5: 6W (60%)

← GPT-4o miniKimi Chat 1.5 →

Kimi Chat 1.5 (5/5)

Intelligence & Reasoning

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

Preference Elo

1,272vs1,420

Coding Elo

—vs1,390

SWE-bench

41.2%vs51%

LiveBench

48.1%vs58%

GPQA Diamond

60.1%vs71.5%

GPT-4o mini: 0WKimi Chat 1.5: 5W

GPT-4o mini (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

160 tok/svs95 tok/s

Time to first token

130 msvs210 ms

GPT-4o mini: 2WKimi Chat 1.5: 0W

GPT-4o mini (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$0.6/1Mvs$0.8/1M

Input price

$0.15/1Mvs$0.2/1M

Context window

128kvs2M

GPT-4o mini: 2WKimi Chat 1.5: 1W

Recommended Workload Routing

Repo / coding agentsKimi Chat 1.5

Higher SWE-bench (51%).

High-volume chatGPT-4o mini

Lower output list price ($0.6/1M).

Voice / low-latency UIGPT-4o mini

Lower TTFT (130 ms).

Long-document RAGKimi Chat 1.5

Larger window (2M).

Screenshots / visionGPT-4o mini

GPT-4o mini is the side marked multimodal in the catalog.

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	Kimi Chat 1.5	Higher SWE-bench (51%).
High-volume chat	GPT-4o mini	Lower output list price ($0.6/1M).
Voice / low-latency UI	GPT-4o mini	Lower TTFT (130 ms).
Long-document RAG	Kimi Chat 1.5	Larger window (2M).
Screenshots / vision	GPT-4o mini	GPT-4o mini is the side marked multimodal in the catalog.

Frequently Asked Questions

Which is better overall, GPT-4o 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-4o mini or Kimi Chat 1.5?

Kimi Chat 1.5 leads SWE-bench at 51% vs 41.2%. SWE-bench is one harness, not your repo.

Which is cheaper to run in production?

GPT-4o mini output tokens are $0.6/1M versus $0.8/1M. Input prices and retry rates still move the real bill.

Which is faster, GPT-4o mini or Kimi Chat 1.5?

GPT-4o mini has the lower time-to-first-token (130 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 128k.

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-4o mini and Kimi Chat 1.5 Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.