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

DeepSeek: DeepSeek V3.1 Terminus vs Gemini 3.6 Flash benchmark

Name: DeepSeek: DeepSeek V3.1 Terminus vs Gemini 3.6 Flash AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

This page compares DeepSeek: DeepSeek V3.1 Terminus (DeepSeek) and Gemini 3.6 Flash (Google) using the latest snapshots we have as of Aug 17, 2026. DeepSeek: DeepSeek V3.1 Terminus wins on output price at $0.95/1M. Gemini 3.6 Flash has the larger context window (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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DeepSeek

DeepSeek: DeepSeek V3.1 Terminus

Auto-discovered from OpenRouter (deepseek/deepseek-v3.1-terminus). Preview until a second source matches.

$0.95/1M out

Google

Gemini 3.6 Flash

Google Jul 21 workhorse. Now shares the 3.7 Flash introductory $0.75/$3.75 rate through Dec 31 2026.

3.6 FlashElo 1,506$3.75/1M out

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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.

DeepSeek: DeepSeek V3.1 Terminus (2)vsGemini 3.6 Flash (8)

DeepSeek: DeepSeek V3.1 Terminus: 2W (20%)Overall: Gemini 3.6 FlashGemini 3.6 Flash: 8W (80%)

← DeepSeek: DeepSeek V3.1 TerminusGemini 3.6 Flash →

Gemini 3.6 Flash (5/5)

Intelligence & Reasoning

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

Preference Elo

—vs1,506

Coding Elo

—vs1,514

SWE-bench

—vs70.8%

LiveBench

—vs67.2%

GPQA Diamond

—vs79.6%

DeepSeek: DeepSeek V3.1 Terminus: 0WGemini 3.6 Flash: 5W

Gemini 3.6 Flash (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

—vs198 tok/s

Time to first token

—vs92 ms

DeepSeek: DeepSeek V3.1 Terminus: 0WGemini 3.6 Flash: 2W

DeepSeek: DeepSeek V3.1 Terminus (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$0.95/1Mvs$3.75/1M

Input price

$0.27/1Mvs$0.75/1M

Context window

164kvs1M

DeepSeek: DeepSeek V3.1 Terminus: 2WGemini 3.6 Flash: 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 AdvantageGemini 3.6 Flash 5/6

Preference Elo

No shared data

Throughput Speed

No shared data

Token Price Efficiency

DeepSeek: DeepSeek V3.1 Terminus

$2.80/1M cheaper

Full Benchmark Score Matrix

—

Elo

High is better

—

EloHigh is better

1,506

Code Elo

High is better

—

Code EloHigh is better

1,514

LiveBench

High is better

—

LiveBenchHigh is better

67.2%

SWE-bench

High is better

—

SWE-benchHigh is better

70.8%

GPQA

High is better

—

GPQAHigh is better

79.6%

TTFT

Low is better

—

TTFTLow is better

92 ms

Speed

High is better

—

SpeedHigh is better

198 tok/s

In $

Low is better

+178%$0.27 / 1M

In $Low is better

$0.75 / 1M

Out $

Low is better

+295%$0.95 / 1M

Out $Low is better

$3.75 / 1M

Context

High is better

164k

ContextHigh is better

1M+540%

Interactive Simulator (USD)

Workload Cost & Savings Calculator

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

Save up to 71% with DeepSeek: DeepSeek V3.1 Terminus

Monthly Volume50M tokens/mo

Quick Presets:

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

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

DeepSeek: DeepSeek V3.1 Terminus$23.70 / mo

In: $9.45Out: $14.25

Gemini 3.6 Flash$82.50 / mo

In: $26.25Out: $56.25

Estimated Cost Delta

DeepSeek: DeepSeek V3.1 Terminus is estimated to save $58.80/month ($706/year).

Based on 50M tokens (30% gen)

Key Selection Recommendations

1
DeepSeek: DeepSeek V3.1 Terminus:Pick DeepSeek: DeepSeek V3.1 Terminus when you are optimizing output cost.
2
Gemini 3.6 Flash:Pick Gemini 3.6 Flash for million-token RAG or long-document jobs.

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatDeepSeek: DeepSeek V3.1 Terminus

Lower output list price ($0.95/1M).

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGGemini 3.6 Flash

Larger window (1M).

Screenshots / visionGemini 3.6 Flash

Gemini 3.6 Flash 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	DeepSeek: DeepSeek V3.1 Terminus	Lower output list price ($0.95/1M).
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	Gemini 3.6 Flash	Larger window (1M).
Screenshots / vision	Gemini 3.6 Flash	Gemini 3.6 Flash is the side marked multimodal in the catalog.

Related Editorial Dispatches & Benchmark Notes

View all news

priceAug 13, 2026

Gemini 3.6 Flash (Jul 21) now shares the 3.7 intro rate

Jul 21 workhorse that inherited $0.75/$3.75 through year-end. Keep the row; 3.7 is the newer sibling.

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LIVE

DeepSeek

DeepSeek: DeepSeek V3.1 Terminus

Elo n/a

LiveBench—

SWE-bench—

Speed—

Output cost$0.95/1M

Google

Gemini 3.6 Flash

Elo 1,506

LiveBench67.2%

SWE-bench70.8%

Speed198 tok/s

Output cost$3.75/1M

Frequently Asked Questions

Which is better overall, DeepSeek: DeepSeek V3.1 Terminus or Gemini 3.6 Flash?: 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, DeepSeek: DeepSeek V3.1 Terminus or Gemini 3.6 Flash?: 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?: DeepSeek: DeepSeek V3.1 Terminus output tokens are $0.95/1M versus $3.75/1M. Input prices and retry rates still move the real bill.
Which is faster, DeepSeek: DeepSeek V3.1 Terminus or Gemini 3.6 Flash?: We do not have TTFT for both models.
Which has the larger context window?: Gemini 3.6 Flash accepts 1M tokens versus 164k.
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. DeepSeek: DeepSeek V3.1 Terminus and Gemini 3.6 Flash Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Similar Head-to-Head Comparisons

All DeepSeek: DeepSeek V3.1 Terminus matchups →|All Gemini 3.6 Flash matchups →

Gemini 3.6 Flash vs Gemini 3 Flash (previous gemini-flash)Gemini 3.6 Flash vs Gemini 3.7 Flash (next gemini-flash)Gemini 3 Pro vs Gemini 3.6 Flash Gemini 2.0 Flash Thinking vs Gemini 3.6 Flash Gemini 3.6 Pro vs Gemini 3.6 Flash DeepSeek V4 Pro vs Gemini 3.6 Flash

DeepSeek: DeepSeek V3.1 Terminus vs Gemini 3.6 Flash benchmark

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

DeepSeek: DeepSeek V3.1 Terminus (2)vsGemini 3.6 Flash (8)

DeepSeek: DeepSeek V3.1 Terminus: 2W (20%)Overall: Gemini 3.6 FlashGemini 3.6 Flash: 8W (80%)

← DeepSeek: DeepSeek V3.1 TerminusGemini 3.6 Flash →

Gemini 3.6 Flash (5/5)

Intelligence & Reasoning

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

Preference Elo

—vs1,506

Coding Elo

—vs1,514

SWE-bench

—vs70.8%

LiveBench

—vs67.2%

GPQA Diamond

—vs79.6%

DeepSeek: DeepSeek V3.1 Terminus: 0WGemini 3.6 Flash: 5W

Gemini 3.6 Flash (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

—vs198 tok/s

Time to first token

—vs92 ms

DeepSeek: DeepSeek V3.1 Terminus: 0WGemini 3.6 Flash: 2W

DeepSeek: DeepSeek V3.1 Terminus (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$0.95/1Mvs$3.75/1M

Input price

$0.27/1Mvs$0.75/1M

Context window

164kvs1M

DeepSeek: DeepSeek V3.1 Terminus: 2WGemini 3.6 Flash: 1W

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatDeepSeek: DeepSeek V3.1 Terminus

Lower output list price ($0.95/1M).

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGGemini 3.6 Flash

Larger window (1M).

Screenshots / visionGemini 3.6 Flash

Gemini 3.6 Flash 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	DeepSeek: DeepSeek V3.1 Terminus	Lower output list price ($0.95/1M).
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	Gemini 3.6 Flash	Larger window (1M).
Screenshots / vision	Gemini 3.6 Flash	Gemini 3.6 Flash is the side marked multimodal in the catalog.

Frequently Asked Questions

Which is better overall, DeepSeek: DeepSeek V3.1 Terminus or Gemini 3.6 Flash?

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, DeepSeek: DeepSeek V3.1 Terminus or Gemini 3.6 Flash?

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?

DeepSeek: DeepSeek V3.1 Terminus output tokens are $0.95/1M versus $3.75/1M. Input prices and retry rates still move the real bill.

Which is faster, DeepSeek: DeepSeek V3.1 Terminus or Gemini 3.6 Flash?

We do not have TTFT for both models.

Which has the larger context window?

Gemini 3.6 Flash accepts 1M tokens versus 164k.

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. DeepSeek: DeepSeek V3.1 Terminus and Gemini 3.6 Flash Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

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

No shared data

No shared data

DeepSeek: DeepSeek V3.1 Terminus

Full Benchmark Score Matrix

Workload Cost & Savings Calculator

Key Selection Recommendations

Recommended Workload Routing

Related Editorial Dispatches & Benchmark Notes

Gemini 3.6 Flash (Jul 21) now shares the 3.7 intro rate

Cast Your Matchup Vote

Community Discussions (0)

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CompareLLM Matrix

DeepSeek: DeepSeek V3.1 Terminus

Gemini 3.6 Flash

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

No shared data

No shared data

DeepSeek: DeepSeek V3.1 Terminus

Full Benchmark Score Matrix

Workload Cost & Savings Calculator

Key Selection Recommendations

Recommended Workload Routing

Related Editorial Dispatches & Benchmark Notes

Gemini 3.6 Flash (Jul 21) now shares the 3.7 intro rate

Cast Your Matchup Vote

Community Discussions (0)

Share card

CompareLLM Matrix

DeepSeek: DeepSeek V3.1 Terminus

Gemini 3.6 Flash

Frequently Asked Questions

Related news

Similar Head-to-Head Comparisons