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

Ernie 4.5 Turbo vs MiniMax: MiniMax M2.7 benchmark

Name: Ernie 4.5 Turbo vs MiniMax: MiniMax M2.7 AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

This page compares Ernie 4.5 Turbo (Baidu) and MiniMax: MiniMax M2.7 (MiniMax) using the latest snapshots we have as of Aug 16, 2026. Ernie 4.5 Turbo wins on output price at $1.2/1M. MiniMax: MiniMax M2.7 has the larger context window (205k 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

Baidu

Ernie 4.5 Turbo

Baidu current multimodal enterprise foundation model with broad Chinese knowledge.

Elo 1,450$1.2/1M out

MiniMax

MiniMax: MiniMax M2.7

Auto-discovered from OpenRouter (minimax/minimax-m2.7). Preview until a second source matches.

$1.2/1M 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.

Ernie 4.5 Turbo (7)vsMiniMax: MiniMax M2.7 (1)

Ernie 4.5 Turbo: 7W (88%)Overall: Ernie 4.5 TurboMiniMax: MiniMax M2.7: 1W (12%)

← Ernie 4.5 Turbo2 tiesMiniMax: MiniMax M2.7 →

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: 5WMiniMax: MiniMax M2.7: 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: 2WMiniMax: MiniMax M2.7: 0W

MiniMax: MiniMax M2.7 (1/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$1.2/1Mvs$1.2/1M

Input price

$0.3/1Mvs$0.3/1M

Context window

128kvs205k

Ernie 4.5 Turbo: 0WMiniMax: MiniMax M2.7: 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 4/6

Preference Elo

No shared data

Throughput Speed

No shared data

Price Efficiency

Ernie 4.5 Turbo

Same token price

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

$0.3/1M

In $Low is better

$0.3/1M

Out $

Low is better

$1.2/1M

Out $Low is better

$1.2/1M

Context

High is better

128k

ContextHigh is better

205k+60%

Interactive Simulator

Workload Cost & Savings Calculator

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

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

MiniMax: MiniMax M2.7$28.50 / mo

In: $10.50Out: $18.00

Key Selection Recommendations

1
Ernie 4.5 Turbo:Pick Ernie 4.5 Turbo when you are optimizing output cost.

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 RAGMiniMax: MiniMax M2.7

Larger window (205k).

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	MiniMax: MiniMax M2.7	Larger window (205k).
Screenshots / vision	Ernie 4.5 Turbo	Ernie 4.5 Turbo 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/ernie-4-5-vs-minimax-m2-7/opengraph-image for crawlers.

PNG

CompareLLM Matrix

Verified head-to-head card

LIVE

Baidu

Ernie 4.5 Turbo

Elo 1,450

LiveBench61%

SWE-bench57%

Speed95 tok/s

Output cost$1.2/1M

MiniMax

MiniMax: MiniMax M2.7

Elo n/a

LiveBench—

SWE-bench—

Speed—

Output cost$1.2/1M

Frequently Asked Questions

Which is better overall, Ernie 4.5 Turbo or MiniMax: MiniMax M2.7?: 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 MiniMax: MiniMax M2.7?: 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 $1.2/1M. Input prices and retry rates still move the real bill.
Which is faster, Ernie 4.5 Turbo or MiniMax: MiniMax M2.7?: We do not have TTFT for both models.
Which has the larger context window?: MiniMax: MiniMax M2.7 accepts 205k 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 MiniMax: MiniMax M2.7 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 MiniMax: MiniMax M2.7 matchups →

Ernie 4.5 Turbo vs Yi-Lightning (previous other)MiniMax M2.5 vs Ernie 4.5 Turbo Mistral Large 3 vs Ernie 4.5 Turbo Doubao Pro 1.5 vs Ernie 4.5 Turbo Gemini 2.0 Flash Thinking vs Ernie 4.5 Turbo Gemini 3 Flash vs Ernie 4.5 Turbo

Ernie 4.5 Turbo vs MiniMax: MiniMax M2.7 benchmark

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

Ernie 4.5 Turbo (7)vsMiniMax: MiniMax M2.7 (1)

Ernie 4.5 Turbo: 7W (88%)Overall: Ernie 4.5 TurboMiniMax: MiniMax M2.7: 1W (12%)

← Ernie 4.5 Turbo2 tiesMiniMax: MiniMax M2.7 →

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: 5WMiniMax: MiniMax M2.7: 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: 2WMiniMax: MiniMax M2.7: 0W

MiniMax: MiniMax M2.7 (1/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$1.2/1Mvs$1.2/1M

Input price

$0.3/1Mvs$0.3/1M

Context window

128kvs205k

Ernie 4.5 Turbo: 0WMiniMax: MiniMax M2.7: 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 RAGMiniMax: MiniMax M2.7

Larger window (205k).

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	MiniMax: MiniMax M2.7	Larger window (205k).
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 MiniMax: MiniMax M2.7?

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 MiniMax: MiniMax M2.7?

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 $1.2/1M. Input prices and retry rates still move the real bill.

Which is faster, Ernie 4.5 Turbo or MiniMax: MiniMax M2.7?

We do not have TTFT for both models.

Which has the larger context window?

MiniMax: MiniMax M2.7 accepts 205k 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 MiniMax: MiniMax M2.7 Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.