Pairwise benchmark snapshot · Aug 17, 2026

Doubao Lite 1.5 vs OpenAI o1-mini benchmark

Name: Doubao Lite 1.5 vs OpenAI o1-mini AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

This page compares Doubao Lite 1.5 (ByteDance) and OpenAI o1-mini (OpenAI) using the latest snapshots we have as of Aug 17, 2026. On preference Elo, OpenAI o1-mini is ahead by 85 points (1,445 vs 1,360; lmarena (Aug 17, 2026)). On SWE-bench coding, OpenAI o1-mini resolves 56.4% versus 46% (swebench (Aug 17, 2026)). Doubao Lite 1.5 streams faster (180 tok/s) while Doubao Lite 1.5 is the cheaper output token ($0.1/1M). OpenAI o1-mini has the larger context window (128k 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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ByteDance

Doubao Lite 1.5

ByteDance high-speed lightweight model priced at sub-cent levels.

Lite 1.5Elo 1,360$0.1/1M out

OpenAI

OpenAI o1-mini

OpenAI high-speed, cost-effective reasoning model optimized for STEM, math, and code generation.

Elo 1,445$4.4/1M out

Model Lineage & Multi-Tier Derivatives🇨🇳 CN Frontier

Doubao Series Family (3 models)

Compare vs Base (Doubao Pro 1.5)

Doubao Pro 1.5

ByteDance

Flagship Base

Elo

1470

Speed

105 tok/s

Price

$0.28 / 1M

View model →vs this

Doubao Lite 1.5

ByteDance

Lite 1.5

Elo

1360

Speed

180 tok/s

Price

$0.10 / 1M

-110 Elo-64% cost1.7x speed

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Seed 2.1 Turbo

ByteDance

Seed 2.1

Elo

1472

Speed

160 tok/s

Price

$2.50 / 1M

+2 Elo+793% cost1.5x speed

View model →vs this

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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.

Doubao Lite 1.5 (4)vsOpenAI o1-mini (6)

Doubao Lite 1.5: 4W (40%)Overall: OpenAI o1-miniOpenAI o1-mini: 6W (60%)

← Doubao Lite 1.5OpenAI o1-mini →

OpenAI o1-mini (5/5)

Intelligence & Reasoning

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

Preference Elo

1,360vs1,445

Coding Elo

1,320vs1,468

SWE-bench

46%vs56.4%

LiveBench

54%vs62%

GPQA Diamond

64.2%vs76.8%

Doubao Lite 1.5: 0WOpenAI o1-mini: 5W

Doubao Lite 1.5 (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

180 tok/svs85 tok/s

Time to first token

110 msvs280 ms

Doubao Lite 1.5: 2WOpenAI o1-mini: 0W

Doubao Lite 1.5 (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$0.1/1Mvs$4.4/1M

Input price

$0.04/1Mvs$1.1/1M

Context window

33kvs128k

Doubao Lite 1.5: 2WOpenAI o1-mini: 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 AdvantageOpenAI o1-mini 4/6

Preference Elo

OpenAI o1-mini

85 pts advantage

Throughput Speed

Doubao Lite 1.5

95 tok/s faster

Token Price Efficiency

Doubao Lite 1.5

$4.30/1M cheaper

Full Benchmark Score Matrix

—

Elo

High is better

1,360

EloHigh is better

1,445+6%

Code Elo

High is better

1,320

Code EloHigh is better

1,468+11%

LiveBench

High is better

54%

LiveBenchHigh is better

62%+15%

SWE-bench

High is better

46%

SWE-benchHigh is better

56.4%+23%

GPQA

High is better

64.2%

GPQAHigh is better

76.8%+20%

TTFT

Low is better

+155%110 ms

TTFTLow is better

280 ms

Speed

High is better

+112%180 tok/s

SpeedHigh is better

85 tok/s

In $

Low is better

+2650%$0.04 / 1M

In $Low is better

$1.10 / 1M

Out $

Low is better

+4300%$0.10 / 1M

Out $Low is better

$4.40 / 1M

Context

High is better

33k

ContextHigh is better

128k+291%

Interactive Simulator (USD)

Workload Cost & Savings Calculator

Simulate monthly production API costs in USD (US Dollar).

Save up to 97% with Doubao Lite 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)

Doubao Lite 1.5$2.90 / mo

In: $1.4Out: $1.5

OpenAI o1-mini$104.50 / mo

In: $38.5Out: $66

Estimated Cost Delta

Doubao Lite 1.5 is estimated to save $101.60/month ($1,219/year).

Based on 50M tokens (30% gen)

Key Selection Recommendations

1
OpenAI o1-mini:Pick OpenAI o1-mini when repo-level coding accuracy is the constraint.
2
Doubao Lite 1.5:Pick Doubao Lite 1.5 when you are optimizing output cost.
3
Doubao Lite 1.5:Pick Doubao Lite 1.5 when time-to-first-token matters more than peak Elo.

Recommended Workload Routing

Repo / coding agentsOpenAI o1-mini

Higher SWE-bench (56.4%).

High-volume chatDoubao Lite 1.5

Lower output list price ($0.1/1M).

Voice / low-latency UIDoubao Lite 1.5

Lower TTFT (110 ms).

Long-document RAGOpenAI o1-mini

Larger window (128k).

Screenshots / visionOpenAI o1-mini

OpenAI o1-mini is the side marked multimodal in the catalog.

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	OpenAI o1-mini	Higher SWE-bench (56.4%).
High-volume chat	Doubao Lite 1.5	Lower output list price ($0.1/1M).
Voice / low-latency UI	Doubao Lite 1.5	Lower TTFT (110 ms).
Long-document RAG	OpenAI o1-mini	Larger window (128k).
Screenshots / vision	OpenAI o1-mini	OpenAI o1-mini is the side marked multimodal in the catalog.

Community Sentiment

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CompareLLM Matrix

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LIVE

ByteDance

Doubao Lite 1.5

Elo 1,360

LiveBench54%

SWE-bench46%

Speed180 tok/s

Output cost$0.1/1M

OpenAI

OpenAI o1-mini

Elo 1,445

LiveBench62%

SWE-bench56.4%

Speed85 tok/s

Output cost$4.4/1M

Frequently Asked Questions

Which is better overall, Doubao Lite 1.5 or OpenAI o1-mini?: OpenAI o1-mini has the higher preference Elo in our latest snapshot (1,445). “Better” still depends on coding, price, and latency — see the table.
Which is better at coding, Doubao Lite 1.5 or OpenAI o1-mini?: OpenAI o1-mini leads SWE-bench at 56.4% vs 46%. SWE-bench is one harness, not your repo.
Which is cheaper to run in production?: Doubao Lite 1.5 output tokens are $0.1/1M versus $4.4/1M. Input prices and retry rates still move the real bill.
Which is faster, Doubao Lite 1.5 or OpenAI o1-mini?: Doubao Lite 1.5 has the lower time-to-first-token (110 ms vs 280 ms). Tokens/sec is a separate column if you care about long completions.
Which has the larger context window?: OpenAI o1-mini accepts 128k tokens versus 33k.
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. Doubao Lite 1.5 and OpenAI o1-mini Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Similar Head-to-Head Comparisons

All Doubao Lite 1.5 matchups →|All OpenAI o1-mini matchups →

Doubao Lite 1.5 vs Doubao Pro 1.5 (next seed)OpenAI o1-mini vs GPT-4o mini (previous gpt-mini)OpenAI o1-mini vs OpenAI: o3 Mini (next gpt-mini)Doubao Pro 1.5 vs OpenAI o1-mini GPT-5 vs OpenAI o1-mini GPT-4.5 Orion vs OpenAI o1-mini

Doubao Lite 1.5 vs OpenAI o1-mini benchmark

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

Doubao Lite 1.5 (4)vsOpenAI o1-mini (6)

Doubao Lite 1.5: 4W (40%)Overall: OpenAI o1-miniOpenAI o1-mini: 6W (60%)

← Doubao Lite 1.5OpenAI o1-mini →

OpenAI o1-mini (5/5)

Intelligence & Reasoning

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

Preference Elo

1,360vs1,445

Coding Elo

1,320vs1,468

SWE-bench

46%vs56.4%

LiveBench

54%vs62%

GPQA Diamond

64.2%vs76.8%

Doubao Lite 1.5: 0WOpenAI o1-mini: 5W

Doubao Lite 1.5 (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

180 tok/svs85 tok/s

Time to first token

110 msvs280 ms

Doubao Lite 1.5: 2WOpenAI o1-mini: 0W

Doubao Lite 1.5 (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$0.1/1Mvs$4.4/1M

Input price

$0.04/1Mvs$1.1/1M

Context window

33kvs128k

Doubao Lite 1.5: 2WOpenAI o1-mini: 1W

Recommended Workload Routing

Repo / coding agentsOpenAI o1-mini

Higher SWE-bench (56.4%).

High-volume chatDoubao Lite 1.5

Lower output list price ($0.1/1M).

Voice / low-latency UIDoubao Lite 1.5

Lower TTFT (110 ms).

Long-document RAGOpenAI o1-mini

Larger window (128k).

Screenshots / visionOpenAI o1-mini

OpenAI o1-mini is the side marked multimodal in the catalog.

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	OpenAI o1-mini	Higher SWE-bench (56.4%).
High-volume chat	Doubao Lite 1.5	Lower output list price ($0.1/1M).
Voice / low-latency UI	Doubao Lite 1.5	Lower TTFT (110 ms).
Long-document RAG	OpenAI o1-mini	Larger window (128k).
Screenshots / vision	OpenAI o1-mini	OpenAI o1-mini is the side marked multimodal in the catalog.

Frequently Asked Questions

Which is better overall, Doubao Lite 1.5 or OpenAI o1-mini?

OpenAI o1-mini has the higher preference Elo in our latest snapshot (1,445). “Better” still depends on coding, price, and latency — see the table.

Which is better at coding, Doubao Lite 1.5 or OpenAI o1-mini?

OpenAI o1-mini leads SWE-bench at 56.4% vs 46%. SWE-bench is one harness, not your repo.

Which is cheaper to run in production?

Doubao Lite 1.5 output tokens are $0.1/1M versus $4.4/1M. Input prices and retry rates still move the real bill.

Which is faster, Doubao Lite 1.5 or OpenAI o1-mini?

Doubao Lite 1.5 has the lower time-to-first-token (110 ms vs 280 ms). Tokens/sec is a separate column if you care about long completions.

Which has the larger context window?

OpenAI o1-mini accepts 128k tokens versus 33k.

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. Doubao Lite 1.5 and OpenAI o1-mini Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.