Pairwise benchmark snapshot · Aug 16, 2026

GPT-4 Turbo vs OpenAI: o1 benchmark

Name: GPT-4 Turbo vs OpenAI: o1 AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

This page compares GPT-4 Turbo (OpenAI) and OpenAI: o1 (OpenAI) using the latest snapshots we have as of Aug 16, 2026. On preference Elo, OpenAI: o1 is ahead by 257 points (1,512 vs 1,255; seed-bootstrap (Aug 1, 2026)). On SWE-bench coding, OpenAI: o1 resolves 48.9% versus 33.2% (seed-bootstrap (Aug 1, 2026)). GPT-4 Turbo streams faster (55 tok/s) while GPT-4 Turbo is the cheaper output token ($30/1M). OpenAI: o1 has the larger context window (200k 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-4 Turbo

GPT-4 Turbo 128k. Historical flagship for gpt-4 turbo vs gpt-4o / gpt-5.

Elo 1,255$30/1M out

OpenAI

OpenAI: o1

Auto-discovered from OpenRouter (openai/o1). Preview until a second source matches.

Elo 1,512$60/1M out

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Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

GPT-4 Turbo (4)vsOpenAI: o1 (6)

GPT-4 Turbo: 4W (40%)Overall: OpenAI: o1OpenAI: o1: 6W (60%)

← GPT-4 TurboOpenAI: o1 →

OpenAI: o1 (5/5)

Intelligence & Reasoning

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

Preference Elo

1,255vs1,512

Coding Elo

—vs1,485

SWE-bench

33.2%vs48.9%

LiveBench

47%vs65.4%

GPQA Diamond

48%vs78%

GPT-4 Turbo: 0WOpenAI: o1: 5W

GPT-4 Turbo (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

55 tok/svs45 tok/s

Time to first token

350 msvs420 ms

GPT-4 Turbo: 2WOpenAI: o1: 0W

GPT-4 Turbo (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$30/1Mvs$60/1M

Input price

$10/1Mvs$15/1M

Context window

128kvs200k

GPT-4 Turbo: 2WOpenAI: o1: 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 4/6

Preference Elo

OpenAI: o1

257 pts advantage

Throughput Speed

GPT-4 Turbo

10 tok/s faster

Price Efficiency

GPT-4 Turbo

$30.00/1M cheaper

Full Benchmark Score Matrix

—

Elo

High is better

1,255

EloHigh is better

1,512+20%

Code Elo

High is better

—

Code EloHigh is better

1,485

LiveBench

High is better

47%

LiveBenchHigh is better

65.4%+39%

SWE-bench

High is better

33.2%

SWE-benchHigh is better

48.9%+47%

GPQA

High is better

48%

GPQAHigh is better

78%+63%

TTFT

Low is better

+20%350 ms

TTFTLow is better

420 ms

Speed

High is better

+22%55 tok/s

SpeedHigh is better

45 tok/s

In $

Low is better

+50%$10/1M

In $Low is better

$15/1M

Out $

Low is better

+100%$30/1M

Out $Low is better

$60/1M

Context

High is better

128k

ContextHigh is better

200k+56%

Interactive Simulator

Workload Cost & Savings Calculator

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

Save up to 44% with GPT-4 Turbo

Monthly Volume50M tokens/mo

Quick Presets:

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

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

GPT-4 Turbo$800.00 / mo

In: $350.00Out: $450.00

OpenAI: o1$1,425.00 / mo

In: $525.00Out: $900.00

Estimated Cost Delta

GPT-4 Turbo is estimated to save $625.00/month ($7,500/year).

Based on 50M tokens (30% gen)

Key Selection Recommendations

1
OpenAI: o1:Pick OpenAI: o1 when repo-level coding accuracy is the constraint.
2
GPT-4 Turbo:Pick GPT-4 Turbo when you are optimizing output cost.
3
GPT-4 Turbo:Pick GPT-4 Turbo when time-to-first-token matters more than peak Elo.

Recommended Workload Routing

Repo / coding agentsOpenAI: o1

Higher SWE-bench (48.9%).

High-volume chatGPT-4 Turbo

Lower output list price ($30/1M).

Voice / low-latency UIGPT-4 Turbo

Lower TTFT (350 ms).

Long-document RAGOpenAI: o1

Larger window (200k).

Screenshots / visionOpenAI: o1

Both accept images. Defaulting to the higher-Elo side (OpenAI: o1).

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	OpenAI: o1	Higher SWE-bench (48.9%).
High-volume chat	GPT-4 Turbo	Lower output list price ($30/1M).
Voice / low-latency UI	GPT-4 Turbo	Lower TTFT (350 ms).
Long-document RAG	OpenAI: o1	Larger window (200k).
Screenshots / vision	OpenAI: o1	Both accept images. Defaulting to the higher-Elo side (OpenAI: o1).

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LIVE

OpenAI

GPT-4 Turbo

Elo 1,255

LiveBench47%

SWE-bench33.2%

Speed55 tok/s

Output cost$30/1M

OpenAI

OpenAI: o1

Elo 1,512

LiveBench65.4%

SWE-bench48.9%

Speed45 tok/s

Output cost$60/1M

Frequently Asked Questions

Which is better overall, GPT-4 Turbo or OpenAI: o1?: OpenAI: o1 has the higher preference Elo in our latest snapshot (1,512). “Better” still depends on coding, price, and latency — see the table.
Which is better at coding, GPT-4 Turbo or OpenAI: o1?: OpenAI: o1 leads SWE-bench at 48.9% vs 33.2%. SWE-bench is one harness, not your repo.
Which is cheaper to run in production?: GPT-4 Turbo output tokens are $30/1M versus $60/1M. Input prices and retry rates still move the real bill.
Which is faster, GPT-4 Turbo or OpenAI: o1?: GPT-4 Turbo has the lower time-to-first-token (350 ms vs 420 ms). Tokens/sec is a separate column if you care about long completions.
Which has the larger context window?: OpenAI: o1 accepts 200k 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-4 Turbo and OpenAI: o1 Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Similar Head-to-Head Comparisons

All GPT-4 Turbo matchups →|All OpenAI: o1 matchups →

GPT-4 Turbo vs GPT-4o (next gpt-flagship)OpenAI: o1 vs GPT-4o (previous gpt-flagship)OpenAI: o1 vs GPT-4.5 Orion (next gpt-flagship)GPT-5 vs OpenAI: o1 GPT-5.6 Sol vs OpenAI: o1 GPT-5.6 Terra vs OpenAI: o1

GPT-4 Turbo vs OpenAI: o1 benchmark

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

GPT-4 Turbo (4)vsOpenAI: o1 (6)

GPT-4 Turbo: 4W (40%)Overall: OpenAI: o1OpenAI: o1: 6W (60%)

← GPT-4 TurboOpenAI: o1 →

OpenAI: o1 (5/5)

Intelligence & Reasoning

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

Preference Elo

1,255vs1,512

Coding Elo

—vs1,485

SWE-bench

33.2%vs48.9%

LiveBench

47%vs65.4%

GPQA Diamond

48%vs78%

GPT-4 Turbo: 0WOpenAI: o1: 5W

GPT-4 Turbo (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

55 tok/svs45 tok/s

Time to first token

350 msvs420 ms

GPT-4 Turbo: 2WOpenAI: o1: 0W

GPT-4 Turbo (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$30/1Mvs$60/1M

Input price

$10/1Mvs$15/1M

Context window

128kvs200k

GPT-4 Turbo: 2WOpenAI: o1: 1W

Recommended Workload Routing

Repo / coding agentsOpenAI: o1

Higher SWE-bench (48.9%).

High-volume chatGPT-4 Turbo

Lower output list price ($30/1M).

Voice / low-latency UIGPT-4 Turbo

Lower TTFT (350 ms).

Long-document RAGOpenAI: o1

Larger window (200k).

Screenshots / visionOpenAI: o1

Both accept images. Defaulting to the higher-Elo side (OpenAI: o1).

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	OpenAI: o1	Higher SWE-bench (48.9%).
High-volume chat	GPT-4 Turbo	Lower output list price ($30/1M).
Voice / low-latency UI	GPT-4 Turbo	Lower TTFT (350 ms).
Long-document RAG	OpenAI: o1	Larger window (200k).
Screenshots / vision	OpenAI: o1	Both accept images. Defaulting to the higher-Elo side (OpenAI: o1).

Frequently Asked Questions

Which is better overall, GPT-4 Turbo or OpenAI: o1?

OpenAI: o1 has the higher preference Elo in our latest snapshot (1,512). “Better” still depends on coding, price, and latency — see the table.

Which is better at coding, GPT-4 Turbo or OpenAI: o1?

OpenAI: o1 leads SWE-bench at 48.9% vs 33.2%. SWE-bench is one harness, not your repo.

Which is cheaper to run in production?

GPT-4 Turbo output tokens are $30/1M versus $60/1M. Input prices and retry rates still move the real bill.

Which is faster, GPT-4 Turbo or OpenAI: o1?

GPT-4 Turbo has the lower time-to-first-token (350 ms vs 420 ms). Tokens/sec is a separate column if you care about long completions.

Which has the larger context window?

OpenAI: o1 accepts 200k 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-4 Turbo and OpenAI: o1 Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.