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

DeepSeek V3 vs FLUX.1 [schnell] benchmark

Name: DeepSeek V3 vs FLUX.1 [schnell] AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

This page compares DeepSeek V3 (DeepSeek) and FLUX.1 [schnell] (Black Forest Labs) using the latest snapshots we have as of Aug 17, 2026. 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 V3

Prior DeepSeek flagship. Baseline for v3 vs v4.

Elo 1,310$1.0287/1M out

Black Forest Labs

FLUX.1 [schnell]

Apache 2.0 4-step distilled open weights model optimized for local inference and instant preview generation.

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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.

DeepSeek V3 (9)vsFLUX.1 [schnell] (0)

DeepSeek V3: 9W (100%)Overall: DeepSeek V3FLUX.1 [schnell]: 0W (0%)

← DeepSeek V3FLUX.1 [schnell] →

DeepSeek V3 (4/5)

Intelligence & Reasoning

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

Preference Elo

1,310vs—

Coding Elo

—vs—

SWE-bench

48.6%vs—

LiveBench

55.4%vs—

GPQA Diamond

59.1%vs—

DeepSeek V3: 4WFLUX.1 [schnell]: 0W

DeepSeek V3 (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

66 tok/svs—

Time to first token

380 msvs—

DeepSeek V3: 2WFLUX.1 [schnell]: 0W

DeepSeek V3 (3/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$1.03/1Mvs—

Input price

$0.26/1Mvs—

Context window

164kvs—

DeepSeek V3: 3WFLUX.1 [schnell]: 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 AdvantageFLUX.1 [schnell] 5/6

Preference Elo

No shared data

Throughput Speed

No shared data

Price Efficiency

No shared data

Full Benchmark Score Matrix

—

Elo

High is better

1,310

EloHigh is better

—

LiveBench

High is better

55.4%

LiveBenchHigh is better

—

SWE-bench

High is better

48.6%

SWE-benchHigh is better

—

GPQA

High is better

59.1%

GPQAHigh is better

—

TTFT

Low is better

380 ms

TTFTLow is better

—

Speed

High is better

66 tok/s

SpeedHigh is better

—

In $

Low is better

$0.26/1M

In $Low is better

—

Out $

Low is better

$1.03/1M

Out $Low is better

—

Context

High is better

164k

ContextHigh is better

—

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatinsufficient data

Need list prices.

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGinsufficient data

Need context sizes.

Screenshots / visionFLUX.1 [schnell]

FLUX.1 [schnell] 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	insufficient data	Need list prices.
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	insufficient data	Need context sizes.
Screenshots / vision	FLUX.1 [schnell]	FLUX.1 [schnell] is the side marked multimodal in the catalog.

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CompareLLM Matrix

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LIVE

DeepSeek

DeepSeek V3

Elo 1,310

LiveBench55.4%

SWE-bench48.6%

Speed66 tok/s

Output cost$1.03/1M

Black Forest Labs

FLUX.1 [schnell]

Elo n/a

LiveBench—

SWE-bench—

Speed—

Output cost—

Frequently Asked Questions

Which is better overall, DeepSeek V3 or FLUX.1 [schnell]?: 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 V3 or FLUX.1 [schnell]?: 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?: List prices are missing for at least one model.
Which is faster, DeepSeek V3 or FLUX.1 [schnell]?: We do not have TTFT for both models.
Which has the larger context window?: Context window is missing for at least one model.
Can I self-host either model?: Both DeepSeek V3 and FLUX.1 [schnell] are marked open-weights. Hosting cost is not in this table.
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 V3 and FLUX.1 [schnell] Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Similar Head-to-Head Comparisons

All DeepSeek V3 matchups →|All FLUX.1 [schnell] matchups →

DeepSeek V3 vs DeepSeek Coder V2 (previous deepseek)DeepSeek V3 vs DeepSeek R1 (next deepseek)FLUX.1 [schnell] vs FLUX.1 [dev] (previous flux)FLUX.1 [schnell] vs FLUX.1.1 [pro] (next flux)DeepSeek V4 Pro vs DeepSeek V3 DeepSeek V4 Flash vs DeepSeek V3

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

DeepSeek V3 (9)vsFLUX.1 [schnell] (0)

DeepSeek V3: 9W (100%)Overall: DeepSeek V3FLUX.1 [schnell]: 0W (0%)

← DeepSeek V3FLUX.1 [schnell] →

DeepSeek V3 (4/5)

Intelligence & Reasoning

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

Preference Elo

1,310vs—

Coding Elo

—vs—

SWE-bench

48.6%vs—

LiveBench

55.4%vs—

GPQA Diamond

59.1%vs—

DeepSeek V3: 4WFLUX.1 [schnell]: 0W

DeepSeek V3 (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

66 tok/svs—

Time to first token

380 msvs—

DeepSeek V3: 2WFLUX.1 [schnell]: 0W

DeepSeek V3 (3/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$1.03/1Mvs—

Input price

$0.26/1Mvs—

Context window

164kvs—

DeepSeek V3: 3WFLUX.1 [schnell]: 0W

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatinsufficient data

Need list prices.

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGinsufficient data

Need context sizes.

Screenshots / visionFLUX.1 [schnell]

FLUX.1 [schnell] 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	insufficient data	Need list prices.
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	insufficient data	Need context sizes.
Screenshots / vision	FLUX.1 [schnell]	FLUX.1 [schnell] is the side marked multimodal in the catalog.

Frequently Asked Questions

Which is better overall, DeepSeek V3 or FLUX.1 [schnell]?

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 V3 or FLUX.1 [schnell]?

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?

List prices are missing for at least one model.

Which is faster, DeepSeek V3 or FLUX.1 [schnell]?

We do not have TTFT for both models.

Which has the larger context window?

Context window is missing for at least one model.

Can I self-host either model?

Both DeepSeek V3 and FLUX.1 [schnell] are marked open-weights. Hosting cost is not in this table.

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 V3 and FLUX.1 [schnell] Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.