Pairwise benchmark snapshot · Aug 16, 2026noindex (thin pair)

Ernie 4.5 Turbo vs OpenAI: GPT-5.6 Terra (batch) benchmark

Name: Ernie 4.5 Turbo vs OpenAI: GPT-5.6 Terra (batch) AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

This page compares Ernie 4.5 Turbo (Baidu) and OpenAI: GPT-5.6 Terra (batch) (OpenAI) using the latest snapshots we have as of Aug 16, 2026. Ernie 4.5 Turbo wins on output price at $1.2/1M. OpenAI: GPT-5.6 Terra (batch) has the larger context window (1.1M 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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Baidu

Ernie 4.5 Turbo

Baidu current multimodal enterprise foundation model with broad Chinese knowledge.

Elo 1,450$1.2/1M out

OpenAI

OpenAI: GPT-5.6 Terra (batch)

Auto-discovered from OpenRouter (openai/gpt-5.6-terra:batch). Preview until a second source matches.

$6/1M out

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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.

Ernie 4.5 Turbo (9)vsOpenAI: GPT-5.6 Terra (batch) (1)

Ernie 4.5 Turbo: 9W (90%)Overall: Ernie 4.5 TurboOpenAI: GPT-5.6 Terra (batch): 1W (10%)

← Ernie 4.5 TurboOpenAI: GPT-5.6 Terra (batch) →

Ernie 4.5 Turbo (5/5)

Intelligence & Reasoning

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

Preference Elo

1,450vs—

Coding Elo

1,435vs—

SWE-bench

57%vs—

LiveBench

61%vs—

GPQA Diamond

74.5%vs—

Ernie 4.5 Turbo: 5WOpenAI: GPT-5.6 Terra (batch): 0W

Ernie 4.5 Turbo (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

95 tok/svs—

Time to first token

200 msvs—

Ernie 4.5 Turbo: 2WOpenAI: GPT-5.6 Terra (batch): 0W

Ernie 4.5 Turbo (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$1.2/1Mvs$6/1M

Input price

$0.3/1Mvs$1/1M

Context window

128kvs1.1M

Ernie 4.5 Turbo: 2WOpenAI: GPT-5.6 Terra (batch): 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 AdvantageErnie 4.5 Turbo 5/6

Preference Elo

No shared data

Throughput Speed

No shared data

Price Efficiency

Ernie 4.5 Turbo

$4.80/1M cheaper

Full Benchmark Score Matrix

—

Elo

High is better

1,450

EloHigh is better

—

Code Elo

High is better

1,435

Code EloHigh is better

—

LiveBench

High is better

61%

LiveBenchHigh is better

—

SWE-bench

High is better

57%

SWE-benchHigh is better

—

GPQA

High is better

74.5%

GPQAHigh is better

—

TTFT

Low is better

200 ms

TTFTLow is better

—

Speed

High is better

95 tok/s

SpeedHigh is better

—

In $

Low is better

+233%$0.3/1M

In $Low is better

$1/1M

Out $

Low is better

+400%$1.2/1M

Out $Low is better

$6/1M

Context

High is better

128k

ContextHigh is better

1.1M+720%

Interactive Simulator

Workload Cost & Savings Calculator

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

Save up to 77% with Ernie 4.5 Turbo

Monthly Volume50M tokens/mo

Quick Presets:

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

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

Ernie 4.5 Turbo$28.50 / mo

In: $10.50Out: $18.00

OpenAI: GPT-5.6 Terra (batch)$125.00 / mo

In: $35.00Out: $90.00

Estimated Cost Delta

Ernie 4.5 Turbo is estimated to save $96.50/month ($1,158/year).

Based on 50M tokens (30% gen)

Key Selection Recommendations

1
Ernie 4.5 Turbo:Pick Ernie 4.5 Turbo when you are optimizing output cost.
2
OpenAI: GPT-5.6 Terra (batch):Pick OpenAI: GPT-5.6 Terra (batch) for million-token RAG or long-document jobs.

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatErnie 4.5 Turbo

Lower output list price ($1.2/1M).

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGOpenAI: GPT-5.6 Terra (batch)

Larger window (1.1M).

Screenshots / visionErnie 4.5 Turbo

Ernie 4.5 Turbo is the side marked multimodal in the catalog.

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	insufficient data	Need SWE-bench on both sides.
High-volume chat	Ernie 4.5 Turbo	Lower output list price ($1.2/1M).
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	OpenAI: GPT-5.6 Terra (batch)	Larger window (1.1M).
Screenshots / vision	Ernie 4.5 Turbo	Ernie 4.5 Turbo is the side marked multimodal in the catalog.

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CompareLLM Matrix

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LIVE

Baidu

Ernie 4.5 Turbo

Elo 1,450

LiveBench61%

SWE-bench57%

Speed95 tok/s

Output cost$1.2/1M

OpenAI

OpenAI: GPT-5.6 Terra (batch)

Elo n/a

LiveBench—

SWE-bench—

Speed—

Output cost$6/1M

Frequently Asked Questions

Which is better overall, Ernie 4.5 Turbo or OpenAI: GPT-5.6 Terra (batch)?: We do not have preference Elo for both models, so we do not declare an overall winner. Compare the metrics that exist.
Which is better at coding, Ernie 4.5 Turbo or OpenAI: GPT-5.6 Terra (batch)?: SWE-bench is missing for at least one model, so we do not rank coding from a single number.
Which is cheaper to run in production?: Ernie 4.5 Turbo output tokens are $1.2/1M versus $6/1M. Input prices and retry rates still move the real bill.
Which is faster, Ernie 4.5 Turbo or OpenAI: GPT-5.6 Terra (batch)?: We do not have TTFT for both models.
Which has the larger context window?: OpenAI: GPT-5.6 Terra (batch) accepts 1.1M 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. Ernie 4.5 Turbo and OpenAI: GPT-5.6 Terra (batch) Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Similar Head-to-Head Comparisons

All Ernie 4.5 Turbo matchups →|All OpenAI: GPT-5.6 Terra (batch) matchups →

Ernie 4.5 Turbo vs Yi-Lightning (previous other)GPT-4.5 Orion vs Ernie 4.5 Turbo GPT-5.6 Terra vs Ernie 4.5 Turbo GPT-5 vs Ernie 4.5 Turbo GPT-5.6 Sol vs Ernie 4.5 Turbo OpenAI o1-mini vs Ernie 4.5 Turbo

Ernie 4.5 Turbo vs OpenAI: GPT-5.6 Terra (batch) benchmark

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

Ernie 4.5 Turbo (9)vsOpenAI: GPT-5.6 Terra (batch) (1)

Ernie 4.5 Turbo: 9W (90%)Overall: Ernie 4.5 TurboOpenAI: GPT-5.6 Terra (batch): 1W (10%)

← Ernie 4.5 TurboOpenAI: GPT-5.6 Terra (batch) →

Ernie 4.5 Turbo (5/5)

Intelligence & Reasoning

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

Preference Elo

1,450vs—

Coding Elo

1,435vs—

SWE-bench

57%vs—

LiveBench

61%vs—

GPQA Diamond

74.5%vs—

Ernie 4.5 Turbo: 5WOpenAI: GPT-5.6 Terra (batch): 0W

Ernie 4.5 Turbo (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

95 tok/svs—

Time to first token

200 msvs—

Ernie 4.5 Turbo: 2WOpenAI: GPT-5.6 Terra (batch): 0W

Ernie 4.5 Turbo (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$1.2/1Mvs$6/1M

Input price

$0.3/1Mvs$1/1M

Context window

128kvs1.1M

Ernie 4.5 Turbo: 2WOpenAI: GPT-5.6 Terra (batch): 1W

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatErnie 4.5 Turbo

Lower output list price ($1.2/1M).

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGOpenAI: GPT-5.6 Terra (batch)

Larger window (1.1M).

Screenshots / visionErnie 4.5 Turbo

Ernie 4.5 Turbo is the side marked multimodal in the catalog.

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	insufficient data	Need SWE-bench on both sides.
High-volume chat	Ernie 4.5 Turbo	Lower output list price ($1.2/1M).
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	OpenAI: GPT-5.6 Terra (batch)	Larger window (1.1M).
Screenshots / vision	Ernie 4.5 Turbo	Ernie 4.5 Turbo is the side marked multimodal in the catalog.

Frequently Asked Questions

Which is better overall, Ernie 4.5 Turbo or OpenAI: GPT-5.6 Terra (batch)?

We do not have preference Elo for both models, so we do not declare an overall winner. Compare the metrics that exist.

Which is better at coding, Ernie 4.5 Turbo or OpenAI: GPT-5.6 Terra (batch)?

SWE-bench is missing for at least one model, so we do not rank coding from a single number.

Which is cheaper to run in production?

Ernie 4.5 Turbo output tokens are $1.2/1M versus $6/1M. Input prices and retry rates still move the real bill.

Which is faster, Ernie 4.5 Turbo or OpenAI: GPT-5.6 Terra (batch)?

We do not have TTFT for both models.

Which has the larger context window?

OpenAI: GPT-5.6 Terra (batch) accepts 1.1M 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. Ernie 4.5 Turbo and OpenAI: GPT-5.6 Terra (batch) Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.