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Every score has a dated snapshot.

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  3. Gemini 3.6 Pro vs MiniMax: MiniMax M1

Pairwise benchmark snapshot · Aug 17, 2026noindex (thin pair)

Gemini 3.6 Pro vs MiniMax: MiniMax M1 benchmark

In this head-to-head showdown, MiniMax: MiniMax M1 is more budget-friendly at $2.2/1M per 1M output tokens. Review the complete breakdown below to determine which model best fits your performance and budget requirements.

Executive Comparison Verdict

Bottom Line: Choose Gemini 3.6 Pro if your priority is peak reasoning, complex code generation, and top preference Elo. Choose MiniMax: MiniMax M1 if you are optimizing for low latency, high throughput, and cost-efficient API deployment.
Share Analysis:
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Google
Gemini 3.6 Pro

Current Google Pro-class multimodal model. Long context, strong coding, billed like the 3.x Pro tier.

Elo 1,570$5/1M out
MiniMax
MiniMax: MiniMax M1

Auto-discovered from OpenRouter (minimax/minimax-m1). Preview until a second source matches.

$2.2/1M out

Gemini 3.6 Pro Thinking Depth & Cost Scaler

Simulate accuracy gains vs added response time & token cost

Mode: Medium (8k tokens)

Reasoning models “think before answering” by generating internal reasoning tokens. Higher effort improves math, coding, and logic accuracy, but increases response delay and token costs.

Thinking Delay
205 ms
Standard speed
Reasoning Depth
~2,400
Internal tokens
Cost / 1k Calls
$14.13
6.6× standard bill
Accuracy Boost
+4.8% accuracy
STEM & SWE-bench
Top Rival Showdowns for Gemini 3.6 Pro
All Matchups
Compare vs:vs Claude Opus 4.5vs GPT-5vs Grok 4.6vs DeepSeek V4 Provs Qwen 3 Max
Preference Leader

No shared data

Single model data

Throughput Leader

No shared data

No latency data

Value per Dollar Leader

MiniMax: MiniMax M1

$2.2 / 1M output

Capability Percentiles

Relative percentile scores computed across all active models in the benchmark catalog.

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 AdvantageGemini 3.6 Pro 5/6
Head-to-Head Comparison

Overall Matchup Breakdown

Category wins across reasoning intelligence, generation speed, and token cost.

Gemini 3.6 Pro (8)vsMiniMax: MiniMax M1 (2)
Gemini 3.6 Pro: 8W (80%)Overall: Gemini 3.6 ProMiniMax: MiniMax M1: 2W (20%)
← Gemini 3.6 ProMiniMax: MiniMax M1 →
Gemini 3.6 Pro (5/5)

Intelligence & Reasoning

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

Preference Elo
1,570vs—
Coding Elo
1,566vs—
SWE-bench
74.6%vs—
LiveBench
71.8%vs—
GPQA Diamond
84.4%vs—
Gemini 3.6 Pro: 5WMiniMax: MiniMax M1: 0W
Gemini 3.6 Pro (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed
102 tok/svs—
Time to first token
205 msvs—
Gemini 3.6 Pro: 2WMiniMax: MiniMax M1: 0W
MiniMax: MiniMax M1 (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price
$5/1Mvs$2.2/1M
Input price
$1.25/1Mvs$0.55/1M
Context window
2Mvs1M
Gemini 3.6 Pro: 1WMiniMax: MiniMax M1: 2W

Side-by-Side Benchmark Matrix

Preference Elo
Gemini 3.6 Pro1,570
lmarena · Aug 16, 2026
MiniMax: MiniMax M1—
Coding Elo
Gemini 3.6 Pro1,566
lmarena · Aug 16, 2026
MiniMax: MiniMax M1—
LiveBench
Gemini 3.6 Pro71.8%
livebench · Aug 16, 2026
MiniMax: MiniMax M1—
SWE-bench
Gemini 3.6 Pro74.6%
swebench · Aug 16, 2026
MiniMax: MiniMax M1—
GPQA Diamond
Gemini 3.6 Pro84.4%
seed-bootstrap · Aug 16, 2026
MiniMax: MiniMax M1—
Time to first token
Gemini 3.6 Pro205 ms
seed-bootstrap · Aug 16, 2026
MiniMax: MiniMax M1—
Output speed
Gemini 3.6 Pro102 tok/s
seed-bootstrap · Aug 16, 2026
MiniMax: MiniMax M1—
Input priceMiniMax: MiniMax M1 (+$0.7/1M)
Gemini 3.6 Pro$1.25/1M
seed-bootstrap · Aug 16, 2026
MiniMax: MiniMax M1$0.55/1M
openrouter · Aug 17, 2026
Output priceMiniMax: MiniMax M1 (+$2.8/1M)
Gemini 3.6 Pro$5/1M
seed-bootstrap · Aug 16, 2026
MiniMax: MiniMax M1$2.2/1M
openrouter · Aug 17, 2026
Context windowGemini 3.6 Pro (+1M)
Gemini 3.6 Pro2M
seed-bootstrap · Aug 16, 2026
MiniMax: MiniMax M11M
openrouter · Aug 17, 2026
BenchmarkGemini 3.6 ProMiniMax: MiniMax M1Advantage Delta
Preference Elo
1,570
lmarena · Aug 16, 2026
——
Coding Elo
1,566
lmarena · Aug 16, 2026
——
LiveBench
71.8%
livebench · Aug 16, 2026
——
SWE-bench
74.6%
swebench · Aug 16, 2026
——
GPQA Diamond
84.4%
seed-bootstrap · Aug 16, 2026
——
Time to first token
205 ms
seed-bootstrap · Aug 16, 2026
——
Output speed
102 tok/s
seed-bootstrap · Aug 16, 2026
——
Input price
$1.25/1M
seed-bootstrap · Aug 16, 2026
$0.55/1M
openrouter · Aug 17, 2026
MiniMax: MiniMax M1 (+$0.7/1M)
Output price
$5/1M
seed-bootstrap · Aug 16, 2026
$2.2/1M
openrouter · Aug 17, 2026
MiniMax: MiniMax M1 (+$2.8/1M)
Context window
2M
seed-bootstrap · Aug 16, 2026
1M
openrouter · Aug 17, 2026
Gemini 3.6 Pro (+1M)
Interactive Simulator (USD)

Workload Cost & Savings Calculator

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

Save up to 56% with MiniMax: MiniMax M1
Monthly Volume50M tokens/mo
Quick Presets:
Token Ratio (In vs Out)70% In / 30% Out
RAG / Search (10% out)Coding / Chat (50% out)
Gemini 3.6 Pro$118.75 / mo
In: $43.75Out: $75
MiniMax: MiniMax M1$52.25 / mo
In: $19.25Out: $33
Estimated Cost Delta

MiniMax: MiniMax M1 is estimated to save $66.50/month ($798/year).

Based on 50M tokens (30% gen)

Key Selection Recommendations

  • 1
    MiniMax: MiniMax M1:Pick MiniMax: MiniMax M1 when you are optimizing output cost.
  • 2
    Gemini 3.6 Pro:Pick Gemini 3.6 Pro for million-token RAG or long-document jobs.

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatMiniMax: MiniMax M1

Lower output list price ($2.2/1M).

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGGemini 3.6 Pro

Larger window (2M).

Screenshots / visionGemini 3.6 Pro

Gemini 3.6 Pro is the side marked multimodal in the catalog.

Target WorkloadRecommended PickEvaluation Rationale
Repo / coding agentsinsufficient dataNeed SWE-bench on both sides.
High-volume chatMiniMax: MiniMax M1Lower output list price ($2.2/1M).
Voice / low-latency UIinsufficient dataNeed TTFT on both sides.
Long-document RAGGemini 3.6 ProLarger window (2M).
Screenshots / visionGemini 3.6 ProGemini 3.6 Pro is the side marked multimodal in the catalog.

Related Editorial Dispatches & Benchmark Notes

View all news
compareAug 13, 2026

Gemini Flash vs Pro: when Flash is the whole product

3.7 Flash vs 3.6 Pro is the current Google volume-versus-upgrade pair.

compareJul 24, 2026

Claude vs Gemini: coding, Elo, and output price — not a brand mashup

Top Anthropic vs top Google. Usually Opus 5 vs 3.6 Pro. Two different invoices.

compareJul 16, 2026

Gemini vs GPT: long context versus the OpenAI flagship invoice

Hub remaps to top Google vs top OpenAI Elo. Usually 3.6 Pro vs Sol. Window vs price is the plot.

launchJul 15, 2026

Gemini 3.6 Pro: Google’s current Pro-class long-context row

2M context, Pro-class Elo and coding. Upgrade path from Flash is this page, not a vibe check.

Community Sentiment

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CompareLLM Matrix

Verified head-to-head card

LIVE
VS
Google

Gemini 3.6 Pro

Elo 1,570
LiveBench71.8%
SWE-bench74.6%
Speed102 tok/s
Output cost$5/1M
MiniMax

MiniMax: MiniMax M1

Elo n/a
LiveBench—
SWE-bench—
Speed—
Output cost$2.2/1M

Frequently Asked Questions

Which is better overall, Gemini 3.6 Pro or MiniMax: MiniMax M1?
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, Gemini 3.6 Pro or MiniMax: MiniMax M1?
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?
MiniMax: MiniMax M1 output tokens are $2.2/1M versus $5/1M. Input prices and retry rates still move the real bill.
Which is faster, Gemini 3.6 Pro or MiniMax: MiniMax M1?
We do not have TTFT for both models.
Which has the larger context window?
Gemini 3.6 Pro accepts 2M tokens versus 1M.
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. Gemini 3.6 Pro and MiniMax: MiniMax M1 Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Related news

  • compare · Aug 13, 2026

    Gemini Flash vs Pro: when Flash is the whole product

  • compare · Jul 24, 2026

    Claude vs Gemini: coding, Elo, and output price — not a brand mashup

  • compare · Jul 16, 2026

    Gemini vs GPT: long context versus the OpenAI flagship invoice

  • launch · Jul 15, 2026

    Gemini 3.6 Pro: Google’s current Pro-class long-context row

Similar Head-to-Head Comparisons

All Gemini 3.6 Pro matchups →|All MiniMax: MiniMax M1 matchups →
Gemini 3.6 Pro vs Gemini 3 Pro (previous gemini-pro)Gemini 3.7 Flash vs Gemini 3.6 ProGemini 3.6 Flash vs Gemini 3.6 ProGemini 3 Flash vs Gemini 3.6 ProGemini 2.0 Flash Thinking vs Gemini 3.6 ProMiniMax M2.5 vs Gemini 3.6 Pro