Pairwise benchmark snapshot · Aug 17, 2026

Gemini 1.5 Pro vs MiniMax M2.5 benchmark

Name: Gemini 1.5 Pro vs MiniMax M2.5 AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

This page compares Gemini 1.5 Pro (Google) and MiniMax M2.5 (MiniMax) using the latest snapshots we have as of Aug 17, 2026. On preference Elo, MiniMax M2.5 is ahead by 218 points (1,478 vs 1,260; lmarena (Aug 17, 2026)). On SWE-bench coding, MiniMax M2.5 resolves 75.8% versus 38% (swebench (Aug 17, 2026)). MiniMax M2.5 streams faster (90 tok/s) while MiniMax M2.5 is the cheaper output token ($0.9/1M). Gemini 1.5 Pro 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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Google

Gemini 1.5 Pro

First million-token Gemini Pro. Baseline for 1.5 vs 2.5 vs 3.x Pro.

Elo 1,260$5/1M out

MiniMax

MiniMax M2.5

MiniMax coding model. Tied near the top of official SWE-bench bash-only in Feb 2026.

Elo 1,478$0.8999999999999999/1M 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.

Gemini 1.5 Pro (2)vsMiniMax M2.5 (8)

Gemini 1.5 Pro: 2W (20%)Overall: MiniMax M2.5MiniMax M2.5: 8W (80%)

← Gemini 1.5 ProMiniMax M2.5 →

MiniMax M2.5 (5/5)

Intelligence & Reasoning

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

Preference Elo

1,260vs1,478

Coding Elo

—vs1,536

SWE-bench

38%vs75.8%

LiveBench

49.2%vs64.4%

GPQA Diamond

58%vs76.2%

Gemini 1.5 Pro: 0WMiniMax M2.5: 5W

Tied (1/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

70 tok/svs90 tok/s

Time to first token

240 msvs250 ms

Gemini 1.5 Pro: 1WMiniMax M2.5: 1W

MiniMax M2.5 (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$5/1Mvs$0.9/1M

Input price

$1.25/1Mvs$0.22/1M

Context window

2Mvs205k

Gemini 1.5 Pro: 1WMiniMax M2.5: 2W

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 AdvantageMiniMax M2.5 5/6

Preference Elo

MiniMax M2.5

218 pts advantage

Throughput Speed

MiniMax M2.5

20 tok/s faster

Token Price Efficiency

MiniMax M2.5

$4.10/1M cheaper

Full Benchmark Score Matrix

—

Elo

High is better

1,260

EloHigh is better

1,478+17%

Code Elo

High is better

—

Code EloHigh is better

1,536

LiveBench

High is better

49.2%

LiveBenchHigh is better

64.4%+31%

SWE-bench

High is better

38%

SWE-benchHigh is better

75.8%+99%

GPQA

High is better

58%

GPQAHigh is better

76.2%+31%

TTFT

Low is better

+4%240 ms

TTFTLow is better

250 ms

Speed

High is better

70 tok/s

SpeedHigh is better

90 tok/s+29%

In $

Low is better

$1.25 / 1M

In $Low is better

$0.22 / 1M+468%

Out $

Low is better

$5.00 / 1M

Out $Low is better

$0.90 / 1M+456%

Context

High is better

+877%2M

ContextHigh is better

205k

Interactive Simulator (USD)

Workload Cost & Savings Calculator

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

Save up to 82% with MiniMax M2.5

Monthly Volume50M tokens/mo

Quick Presets:

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

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

Gemini 1.5 Pro$118.75 / mo

In: $43.75Out: $75

MiniMax M2.5$21.20 / mo

In: $7.7Out: $13.5

Estimated Cost Delta

MiniMax M2.5 is estimated to save $97.55/month ($1,171/year).

Based on 50M tokens (30% gen)

Key Selection Recommendations

1
MiniMax M2.5:Pick MiniMax M2.5 when repo-level coding accuracy is the constraint.
2
Gemini 1.5 Pro:Pick Gemini 1.5 Pro when time-to-first-token matters more than peak Elo.
3
Gemini 1.5 Pro:Pick Gemini 1.5 Pro for million-token RAG or long-document jobs.

Recommended Workload Routing

Repo / coding agentsMiniMax M2.5

Higher SWE-bench (75.8%).

High-volume chatMiniMax M2.5

Lower output list price ($0.9/1M).

Voice / low-latency UIGemini 1.5 Pro

Lower TTFT (240 ms).

Long-document RAGGemini 1.5 Pro

Larger window (2M).

Screenshots / visionGemini 1.5 Pro

Gemini 1.5 Pro is the side marked multimodal in the catalog.

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	MiniMax M2.5	Higher SWE-bench (75.8%).
High-volume chat	MiniMax M2.5	Lower output list price ($0.9/1M).
Voice / low-latency UI	Gemini 1.5 Pro	Lower TTFT (240 ms).
Long-document RAG	Gemini 1.5 Pro	Larger window (2M).
Screenshots / vision	Gemini 1.5 Pro	Gemini 1.5 Pro is the side marked multimodal in the catalog.

Related Editorial Dispatches & Benchmark Notes

View all news

launchFeb 12, 2026

MiniMax M2.5: the Feb 2026 SWE-bench specialist still on the board

Tied near the top of official SWE-bench bash-only in Feb 2026. Coding lists should still see it.

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LIVE

Google

Gemini 1.5 Pro

Elo 1,260

LiveBench49.2%

SWE-bench38%

Speed70 tok/s

Output cost$5/1M

MiniMax

MiniMax M2.5

Elo 1,478

LiveBench64.4%

SWE-bench75.8%

Speed90 tok/s

Output cost$0.9/1M

Frequently Asked Questions

Which is better overall, Gemini 1.5 Pro or MiniMax M2.5?: MiniMax M2.5 has the higher preference Elo in our latest snapshot (1,478). “Better” still depends on coding, price, and latency — see the table.
Which is better at coding, Gemini 1.5 Pro or MiniMax M2.5?: MiniMax M2.5 leads SWE-bench at 75.8% vs 38%. SWE-bench is one harness, not your repo.
Which is cheaper to run in production?: MiniMax M2.5 output tokens are $0.9/1M versus $5/1M. Input prices and retry rates still move the real bill.
Which is faster, Gemini 1.5 Pro or MiniMax M2.5?: Gemini 1.5 Pro has the lower time-to-first-token (240 ms vs 250 ms). Tokens/sec is a separate column if you care about long completions.
Which has the larger context window?: Gemini 1.5 Pro accepts 2M tokens versus 205k.
Can I self-host either model?: MiniMax M2.5 is marked open-weights in our catalog. The other side is a closed API. Check the provider license before you ship weights.
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. Gemini 1.5 Pro and MiniMax M2.5 Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Similar Head-to-Head Comparisons

All Gemini 1.5 Pro matchups →|All MiniMax M2.5 matchups →

Gemini 1.5 Pro vs Gemini 2.5 Pro (next gemini-pro)Gemini 3 Pro vs MiniMax M2.5 Gemini 3 Flash vs MiniMax M2.5 Gemini 2.0 Flash Thinking vs MiniMax M2.5 Gemini 3.6 Pro vs MiniMax M2.5 Gemini 3.6 Flash vs MiniMax M2.5

Gemini 1.5 Pro vs MiniMax M2.5 benchmark

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

Gemini 1.5 Pro (2)vsMiniMax M2.5 (8)

Gemini 1.5 Pro: 2W (20%)Overall: MiniMax M2.5MiniMax M2.5: 8W (80%)

← Gemini 1.5 ProMiniMax M2.5 →

MiniMax M2.5 (5/5)

Intelligence & Reasoning

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

Preference Elo

1,260vs1,478

Coding Elo

—vs1,536

SWE-bench

38%vs75.8%

LiveBench

49.2%vs64.4%

GPQA Diamond

58%vs76.2%

Gemini 1.5 Pro: 0WMiniMax M2.5: 5W

Tied (1/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

70 tok/svs90 tok/s

Time to first token

240 msvs250 ms

Gemini 1.5 Pro: 1WMiniMax M2.5: 1W

MiniMax M2.5 (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$5/1Mvs$0.9/1M

Input price

$1.25/1Mvs$0.22/1M

Context window

2Mvs205k

Gemini 1.5 Pro: 1WMiniMax M2.5: 2W

Recommended Workload Routing

Repo / coding agentsMiniMax M2.5

Higher SWE-bench (75.8%).

High-volume chatMiniMax M2.5

Lower output list price ($0.9/1M).

Voice / low-latency UIGemini 1.5 Pro

Lower TTFT (240 ms).

Long-document RAGGemini 1.5 Pro

Larger window (2M).

Screenshots / visionGemini 1.5 Pro

Gemini 1.5 Pro is the side marked multimodal in the catalog.

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	MiniMax M2.5	Higher SWE-bench (75.8%).
High-volume chat	MiniMax M2.5	Lower output list price ($0.9/1M).
Voice / low-latency UI	Gemini 1.5 Pro	Lower TTFT (240 ms).
Long-document RAG	Gemini 1.5 Pro	Larger window (2M).
Screenshots / vision	Gemini 1.5 Pro	Gemini 1.5 Pro is the side marked multimodal in the catalog.

Frequently Asked Questions

Which is better overall, Gemini 1.5 Pro or MiniMax M2.5?

MiniMax M2.5 has the higher preference Elo in our latest snapshot (1,478). “Better” still depends on coding, price, and latency — see the table.

Which is better at coding, Gemini 1.5 Pro or MiniMax M2.5?

MiniMax M2.5 leads SWE-bench at 75.8% vs 38%. SWE-bench is one harness, not your repo.

Which is cheaper to run in production?

MiniMax M2.5 output tokens are $0.9/1M versus $5/1M. Input prices and retry rates still move the real bill.

Which is faster, Gemini 1.5 Pro or MiniMax M2.5?

Gemini 1.5 Pro has the lower time-to-first-token (240 ms vs 250 ms). Tokens/sec is a separate column if you care about long completions.

Which has the larger context window?

Gemini 1.5 Pro accepts 2M tokens versus 205k.

Can I self-host either model?

MiniMax M2.5 is marked open-weights in our catalog. The other side is a closed API. Check the provider license before you ship weights.

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. Gemini 1.5 Pro and MiniMax M2.5 Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

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Interactive Comparison Diagram

Tug-of-War Matchup Matrix

Intelligence & Reasoning

Speed & Latency

Pricing & Capacity

Multi-Dimensional Capability Radar

MiniMax M2.5

MiniMax M2.5

MiniMax M2.5

Full Benchmark Score Matrix

Workload Cost & Savings Calculator

Key Selection Recommendations

Recommended Workload Routing

Related Editorial Dispatches & Benchmark Notes

MiniMax M2.5: the Feb 2026 SWE-bench specialist still on the board

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CompareLLM Matrix

Gemini 1.5 Pro

MiniMax M2.5

Frequently Asked Questions

Related news

Similar Head-to-Head Comparisons

Swap or Add Any Model to this Matchup

Interactive Comparison Diagram

Tug-of-War Matchup Matrix

Intelligence & Reasoning

Speed & Latency

Pricing & Capacity

Multi-Dimensional Capability Radar

MiniMax M2.5

MiniMax M2.5

MiniMax M2.5

Full Benchmark Score Matrix

Workload Cost & Savings Calculator

Key Selection Recommendations

Recommended Workload Routing

Related Editorial Dispatches & Benchmark Notes

MiniMax M2.5: the Feb 2026 SWE-bench specialist still on the board

Cast Your Matchup Vote

Community Discussions (0)

Share card

CompareLLM Matrix

Gemini 1.5 Pro

MiniMax M2.5

Frequently Asked Questions

Related news

Similar Head-to-Head Comparisons