Pairwise benchmark snapshot · Aug 16, 2026

MiniMax M2.5 vs OpenAI: o1 benchmark

Name: MiniMax M2.5 vs OpenAI: o1 AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

This page compares MiniMax M2.5 (MiniMax) and OpenAI: o1 (OpenAI) using the latest snapshots we have as of Aug 16, 2026. On preference Elo, OpenAI: o1 is ahead by 34 points (1,512 vs 1,478; seed-bootstrap (Aug 1, 2026)). On SWE-bench coding, MiniMax M2.5 resolves 75.8% versus 48.9% (seed-bootstrap (Aug 1, 2026)). MiniMax M2.5 streams faster (90 tok/s) while MiniMax M2.5 is the cheaper output token ($0.9/1M). MiniMax M2.5 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.

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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

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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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.

MiniMax M2.5 (7)vsOpenAI: o1 (3)

MiniMax M2.5: 7W (70%)Overall: MiniMax M2.5OpenAI: o1: 3W (30%)

← MiniMax M2.5OpenAI: o1 →

OpenAI: o1 (3/5)

Intelligence & Reasoning

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

Preference Elo

1,478vs1,512

Coding Elo

1,536vs1,485

SWE-bench

75.8%vs48.9%

LiveBench

64.4%vs65.4%

GPQA Diamond

76.2%vs78%

MiniMax M2.5: 2WOpenAI: o1: 3W

MiniMax M2.5 (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

90 tok/svs45 tok/s

Time to first token

250 msvs420 ms

MiniMax M2.5: 2WOpenAI: o1: 0W

MiniMax M2.5 (3/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$0.9/1Mvs$60/1M

Input price

$0.22/1Mvs$15/1M

Context window

205kvs200k

MiniMax M2.5: 3WOpenAI: o1: 0W

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 4/6

Preference Elo

OpenAI: o1

34 pts advantage

Throughput Speed

MiniMax M2.5

45 tok/s faster

Price Efficiency

MiniMax M2.5

$59.10/1M cheaper

Full Benchmark Score Matrix

—

Elo

High is better

1,478

EloHigh is better

1,512+2%

Code Elo

High is better

+3%1,536

Code EloHigh is better

1,485

LiveBench

High is better

64.4%

LiveBenchHigh is better

65.4%+2%

SWE-bench

High is better

+55%75.8%

SWE-benchHigh is better

48.9%

GPQA

High is better

76.2%

GPQAHigh is better

78%+2%

TTFT

Low is better

+68%250 ms

TTFTLow is better

420 ms

Speed

High is better

+100%90 tok/s

SpeedHigh is better

45 tok/s

In $

Low is better

+6718%$0.22/1M

In $Low is better

$15/1M

Out $

Low is better

+6567%$0.9/1M

Out $Low is better

$60/1M

Context

High is better

+2%205k

ContextHigh is better

200k

Interactive Simulator

Workload Cost & Savings Calculator

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

Save up to 99% 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)

MiniMax M2.5$21.20 / mo

In: $7.70Out: $13.50

OpenAI: o1$1,425.00 / mo

In: $525.00Out: $900.00

Estimated Cost Delta

MiniMax M2.5 is estimated to save $1,403.80/month ($16,846/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
MiniMax M2.5:Pick MiniMax M2.5 when time-to-first-token matters more than peak Elo.
3
OpenAI: o1:Pick OpenAI: o1 as the default general assistant.

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 UIMiniMax M2.5

Lower TTFT (250 ms).

Long-document RAGMiniMax M2.5

Larger window (205k).

Screenshots / visionOpenAI: o1

OpenAI: o1 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	MiniMax M2.5	Lower TTFT (250 ms).
Long-document RAG	MiniMax M2.5	Larger window (205k).
Screenshots / vision	OpenAI: o1	OpenAI: o1 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

MiniMax

MiniMax M2.5

Elo 1,478

LiveBench64.4%

SWE-bench75.8%

Speed90 tok/s

Output cost$0.9/1M

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, MiniMax M2.5 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, MiniMax M2.5 or OpenAI: o1?: MiniMax M2.5 leads SWE-bench at 75.8% vs 48.9%. 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 $60/1M. Input prices and retry rates still move the real bill.
Which is faster, MiniMax M2.5 or OpenAI: o1?: MiniMax M2.5 has the lower time-to-first-token (250 ms vs 420 ms). Tokens/sec is a separate column if you care about long completions.
Which has the larger context window?: MiniMax M2.5 accepts 205k tokens versus 200k.
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. MiniMax M2.5 and OpenAI: o1 Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Similar Head-to-Head Comparisons

All MiniMax M2.5 matchups →|All OpenAI: o1 matchups →

OpenAI: o1 vs GPT-4o (previous gpt-flagship)OpenAI: o1 vs GPT-4.5 Orion (next gpt-flagship)GPT-5.6 Terra vs OpenAI: o1 GPT-5 vs OpenAI: o1 GPT-5.6 Sol vs OpenAI: o1 GPT-5.6 Luna vs MiniMax M2.5

MiniMax M2.5 vs OpenAI: o1 benchmark

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

MiniMax M2.5 (7)vsOpenAI: o1 (3)

MiniMax M2.5: 7W (70%)Overall: MiniMax M2.5OpenAI: o1: 3W (30%)

← MiniMax M2.5OpenAI: o1 →

OpenAI: o1 (3/5)

Intelligence & Reasoning

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

Preference Elo

1,478vs1,512

Coding Elo

1,536vs1,485

SWE-bench

75.8%vs48.9%

LiveBench

64.4%vs65.4%

GPQA Diamond

76.2%vs78%

MiniMax M2.5: 2WOpenAI: o1: 3W

MiniMax M2.5 (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

90 tok/svs45 tok/s

Time to first token

250 msvs420 ms

MiniMax M2.5: 2WOpenAI: o1: 0W

MiniMax M2.5 (3/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$0.9/1Mvs$60/1M

Input price

$0.22/1Mvs$15/1M

Context window

205kvs200k

MiniMax M2.5: 3WOpenAI: o1: 0W

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 UIMiniMax M2.5

Lower TTFT (250 ms).

Long-document RAGMiniMax M2.5

Larger window (205k).

Screenshots / visionOpenAI: o1

OpenAI: o1 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	MiniMax M2.5	Lower TTFT (250 ms).
Long-document RAG	MiniMax M2.5	Larger window (205k).
Screenshots / vision	OpenAI: o1	OpenAI: o1 is the side marked multimodal in the catalog.

Frequently Asked Questions

Which is better overall, MiniMax M2.5 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, MiniMax M2.5 or OpenAI: o1?

MiniMax M2.5 leads SWE-bench at 75.8% vs 48.9%. 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 $60/1M. Input prices and retry rates still move the real bill.

Which is faster, MiniMax M2.5 or OpenAI: o1?

MiniMax M2.5 has the lower time-to-first-token (250 ms vs 420 ms). Tokens/sec is a separate column if you care about long completions.

Which has the larger context window?

MiniMax M2.5 accepts 205k tokens versus 200k.

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. MiniMax M2.5 and OpenAI: o1 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

OpenAI: o1

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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MiniMax M2.5

OpenAI: o1

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

OpenAI: o1

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

MiniMax M2.5

OpenAI: o1

Frequently Asked Questions

Related news

Similar Head-to-Head Comparisons