Pairwise benchmark snapshot · Aug 16, 2026

Kimi Chat 1.5 vs OpenAI: o3 Mini benchmark

Name: Kimi Chat 1.5 vs OpenAI: o3 Mini AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

This page compares Kimi Chat 1.5 (Moonshot) and OpenAI: o3 Mini (OpenAI) using the latest snapshots we have as of Aug 16, 2026. On preference Elo, OpenAI: o3 Mini is ahead by 140 points (1,560 vs 1,420; seed-bootstrap (Aug 1, 2026)). On SWE-bench coding, OpenAI: o3 Mini resolves 78.5% versus 51% (seed-bootstrap (Aug 1, 2026)). Kimi Chat 1.5 streams faster (95 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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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

OpenAI

OpenAI: o3 Mini

Auto-discovered from OpenRouter (openai/o3-mini). Preview until a second source matches.

Elo 1,560$4.4/1M out

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Model A

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Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

Kimi Chat 1.5 (5)vsOpenAI: o3 Mini (5)

Kimi Chat 1.5: 5W (50%)Overall: Even matchupOpenAI: o3 Mini: 5W (50%)

← Kimi Chat 1.5OpenAI: o3 Mini →

OpenAI: o3 Mini (5/5)

Intelligence & Reasoning

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

Preference Elo

1,420vs1,560

Coding Elo

1,390vs1,585

SWE-bench

51%vs78.5%

LiveBench

58%vs72.4%

GPQA Diamond

71.5%vs87.2%

Kimi Chat 1.5: 0WOpenAI: o3 Mini: 5W

Kimi Chat 1.5 (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

95 tok/svs92 tok/s

Time to first token

210 msvs290 ms

Kimi Chat 1.5: 2WOpenAI: o3 Mini: 0W

Kimi Chat 1.5 (3/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$0.8/1Mvs$4.4/1M

Input price

$0.2/1Mvs$1.1/1M

Context window

2Mvs200k

Kimi Chat 1.5: 3WOpenAI: o3 Mini: 0W

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 AdvantageEven 3–3

Preference Elo

OpenAI: o3 Mini

140 pts advantage

Throughput Speed

Kimi Chat 1.5

3 tok/s faster

Price Efficiency

Kimi Chat 1.5

$3.60/1M cheaper

Full Benchmark Score Matrix

—

Elo

High is better

1,420

EloHigh is better

1,560+10%

Code Elo

High is better

1,390

Code EloHigh is better

1,585+14%

LiveBench

High is better

58%

LiveBenchHigh is better

72.4%+25%

SWE-bench

High is better

51%

SWE-benchHigh is better

78.5%+54%

GPQA

High is better

71.5%

GPQAHigh is better

87.2%+22%

TTFT

Low is better

+38%210 ms

TTFTLow is better

290 ms

Speed

High is better

+3%95 tok/s

SpeedHigh is better

92 tok/s

In $

Low is better

+450%$0.2/1M

In $Low is better

$1.1/1M

Out $

Low is better

+450%$0.8/1M

Out $Low is better

$4.4/1M

Context

High is better

+900%2M

ContextHigh is better

200k

Interactive Simulator

Workload Cost & Savings Calculator

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

Save up to 82% 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)

Kimi Chat 1.5$19.00 / mo

In: $7.00Out: $12.00

OpenAI: o3 Mini$104.50 / mo

In: $38.50Out: $66.00

Estimated Cost Delta

Kimi Chat 1.5 is estimated to save $85.50/month ($1,026/year).

Based on 50M tokens (30% gen)

Key Selection Recommendations

1
OpenAI: o3 Mini:Pick OpenAI: o3 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
Kimi Chat 1.5:Pick Kimi Chat 1.5 when time-to-first-token matters more than peak Elo.

Recommended Workload Routing

Repo / coding agentsOpenAI: o3 Mini

Higher SWE-bench (78.5%).

High-volume chatKimi Chat 1.5

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

Voice / low-latency UIKimi Chat 1.5

Lower TTFT (210 ms).

Long-document RAGKimi Chat 1.5

Larger window (2M).

Screenshots / visionOpenAI: o3 Mini

OpenAI: o3 Mini is the side marked multimodal in the catalog.

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	OpenAI: o3 Mini	Higher SWE-bench (78.5%).
High-volume chat	Kimi Chat 1.5	Lower output list price ($0.8/1M).
Voice / low-latency UI	Kimi Chat 1.5	Lower TTFT (210 ms).
Long-document RAG	Kimi Chat 1.5	Larger window (2M).
Screenshots / vision	OpenAI: o3 Mini	OpenAI: o3 Mini is the side marked multimodal in the catalog.

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LIVE

Moonshot

Kimi Chat 1.5

Elo 1,420

LiveBench58%

SWE-bench51%

Speed95 tok/s

Output cost$0.8/1M

OpenAI

OpenAI: o3 Mini

Elo 1,560

LiveBench72.4%

SWE-bench78.5%

Speed92 tok/s

Output cost$4.4/1M

Frequently Asked Questions

Which is better overall, Kimi Chat 1.5 or OpenAI: o3 Mini?: OpenAI: o3 Mini has the higher preference Elo in our latest snapshot (1,560). “Better” still depends on coding, price, and latency — see the table.
Which is better at coding, Kimi Chat 1.5 or OpenAI: o3 Mini?: OpenAI: o3 Mini leads SWE-bench at 78.5% 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 $4.4/1M. Input prices and retry rates still move the real bill.
Which is faster, Kimi Chat 1.5 or OpenAI: o3 Mini?: Kimi Chat 1.5 has the lower time-to-first-token (210 ms vs 290 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 200k.
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. Kimi Chat 1.5 and OpenAI: o3 Mini Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Similar Head-to-Head Comparisons

All Kimi Chat 1.5 matchups →|All OpenAI: o3 Mini matchups →

Kimi Chat 1.5 vs MoonshotAI: Kimi K2 0711 (next kimi)OpenAI: o3 Mini vs OpenAI o1-mini (previous gpt-mini)OpenAI: o3 Mini vs GPT-5 mini (next gpt-mini)Kimi K3 vs OpenAI: o3 Mini GPT-4.5 Orion vs OpenAI: o3 Mini GPT-5.6 Terra vs OpenAI: o3 Mini

Kimi Chat 1.5 vs OpenAI: o3 Mini benchmark

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

Kimi Chat 1.5 (5)vsOpenAI: o3 Mini (5)

Kimi Chat 1.5: 5W (50%)Overall: Even matchupOpenAI: o3 Mini: 5W (50%)

← Kimi Chat 1.5OpenAI: o3 Mini →

OpenAI: o3 Mini (5/5)

Intelligence & Reasoning

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

Preference Elo

1,420vs1,560

Coding Elo

1,390vs1,585

SWE-bench

51%vs78.5%

LiveBench

58%vs72.4%

GPQA Diamond

71.5%vs87.2%

Kimi Chat 1.5: 0WOpenAI: o3 Mini: 5W

Kimi Chat 1.5 (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

95 tok/svs92 tok/s

Time to first token

210 msvs290 ms

Kimi Chat 1.5: 2WOpenAI: o3 Mini: 0W

Kimi Chat 1.5 (3/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$0.8/1Mvs$4.4/1M

Input price

$0.2/1Mvs$1.1/1M

Context window

2Mvs200k

Kimi Chat 1.5: 3WOpenAI: o3 Mini: 0W

Recommended Workload Routing

Repo / coding agentsOpenAI: o3 Mini

Higher SWE-bench (78.5%).

High-volume chatKimi Chat 1.5

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

Voice / low-latency UIKimi Chat 1.5

Lower TTFT (210 ms).

Long-document RAGKimi Chat 1.5

Larger window (2M).

Screenshots / visionOpenAI: o3 Mini

OpenAI: o3 Mini is the side marked multimodal in the catalog.

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	OpenAI: o3 Mini	Higher SWE-bench (78.5%).
High-volume chat	Kimi Chat 1.5	Lower output list price ($0.8/1M).
Voice / low-latency UI	Kimi Chat 1.5	Lower TTFT (210 ms).
Long-document RAG	Kimi Chat 1.5	Larger window (2M).
Screenshots / vision	OpenAI: o3 Mini	OpenAI: o3 Mini is the side marked multimodal in the catalog.

Frequently Asked Questions

Which is better overall, Kimi Chat 1.5 or OpenAI: o3 Mini?

OpenAI: o3 Mini has the higher preference Elo in our latest snapshot (1,560). “Better” still depends on coding, price, and latency — see the table.

Which is better at coding, Kimi Chat 1.5 or OpenAI: o3 Mini?

OpenAI: o3 Mini leads SWE-bench at 78.5% 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 $4.4/1M. Input prices and retry rates still move the real bill.

Which is faster, Kimi Chat 1.5 or OpenAI: o3 Mini?

Kimi Chat 1.5 has the lower time-to-first-token (210 ms vs 290 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 200k.

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. Kimi Chat 1.5 and OpenAI: o3 Mini Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.