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

FLUX.2 [flex] vs Llama 3.1 70B benchmark

Name: FLUX.2 [flex] vs Llama 3.1 70B AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

Comparing verified benchmark accuracy, speed, and token pricing between FLUX.2 [flex] and Llama 3.1 70B. Review the complete breakdown below to determine which model best fits your performance and budget requirements.

Share Analysis:

Black Forest Labs

FLUX.2 [flex]

Flexible step-distilled variant of FLUX.2 offering 99% of Max quality with 45% faster generation speeds.

Flex / TurboImg Elo 1,224$60/1k imgs

FLUX.2 Series Family & Variants (2)

Speed, cost, and intelligence tradeoffs across the Black Forest Labs lineup

vs Base Model

FLUX.2 [max]

Black Forest Labs

Base Model

Img Elo1233

Latency5.1s

$/1k$70/1k

Prompt %91.2%

View specs →vs this

FLUX.2 [flex]

Black Forest Labs

Flex / Turbo

Img Elo1224

Latency2.8s

$/1k$60/1k

Prompt %90.5%

-9 Elo-14% price

Selected

Top Rival Showdowns for FLUX.2 [flex]

All Matchups

Compare vs:vs GPT Image 2 (High)vs Reve 2.1 vs Nano Banana Pro (Gemini 3 Pro Image)vs Ideogram 4.0 (Quality)vs Recraft V4.1 Utility Pro

Image Quality Leader

No shared data

Single model data

Generation Speed Leader

No shared data

No latency data

Value per Dollar Leader

No shared data

Unpriced

Head-to-Head Comparison

Overall Matchup Breakdown

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

FLUX.2 [flex] (5)vsLlama 3.1 70B (0)

FLUX.2 [flex]: 5W (100%)Overall: FLUX.2 [flex]Llama 3.1 70B: 0W (0%)

← FLUX.2 [flex]Llama 3.1 70B →

FLUX.2 [flex] (3/3)

Visual Quality & Adherence

Arena Preference Elo, prompt fidelity & typography score

Image Elo

1,224vs—

Prompt adherence

90.5%vs—

Text rendering

91.5%vs—

FLUX.2 [flex]: 3WLlama 3.1 70B: 0W

FLUX.2 [flex] (1/1)

Generation Latency

Time to render full-resolution image snapshot (seconds)

Generation time

2.8svs—

FLUX.2 [flex]: 1WLlama 3.1 70B: 0W

FLUX.2 [flex] (1/1)

Cost Efficiency

API inference cost per 1,000 generated images

Price per 1k images

$60/1kvs—

FLUX.2 [flex]: 1WLlama 3.1 70B: 0W

Side-by-Side Benchmark Matrix

Image Elo

FLUX.2 [flex]1,224

seed-bootstrap · Aug 1, 2026

Llama 3.1 70B—

Generation time

FLUX.2 [flex]2.8s

seed-bootstrap · Aug 1, 2026

Llama 3.1 70B—

Price per 1k images

FLUX.2 [flex]$60/1k

seed-bootstrap · Aug 1, 2026

Llama 3.1 70B—

Prompt adherence

FLUX.2 [flex]90.5%

seed-bootstrap · Aug 1, 2026

Llama 3.1 70B—

Text rendering

FLUX.2 [flex]91.5%

seed-bootstrap · Aug 1, 2026

Llama 3.1 70B—

Benchmark	FLUX.2 [flex]	Llama 3.1 70B	Advantage Delta
Image Elo	1,224 seed-bootstrap · Aug 1, 2026	—	—
Generation time	2.8s seed-bootstrap · Aug 1, 2026	—	—
Price per 1k images	$60/1k seed-bootstrap · Aug 1, 2026	—	—
Prompt adherence	90.5% seed-bootstrap · Aug 1, 2026	—	—
Text rendering	91.5% seed-bootstrap · Aug 1, 2026	—	—

Interactive Simulator (USD)

Workload Cost & Savings Calculator

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

Save up to 100% with Llama 3.1 70B

Monthly Image Production Volume25k images / month (25000 imgs)

Quick Presets:

FLUX.2 [flex]$1,500.00 / mo

Rate: $60/1k

Llama 3.1 70B$0.00 / mo

Rate: $0/1k

Estimated Cost Delta

Llama 3.1 70B is estimated to save $1,500.00/month ($18,000/year).

Based on 25k images generated

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.2 [flex]

FLUX.2 [flex] 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.2 [flex]	FLUX.2 [flex] is the side marked multimodal in the catalog.

Community Sentiment

Cast Your Matchup Vote

0 total votes

Community Discussions (0)

No comments posted on this matchup yet. Be the first to share an evaluation note!

Share card

The real PNG is generated at /compare/flux-2-flex-vs-llama-3-1-70b/opengraph-image for crawlers.

PNG

CompareLLM Matrix

Verified head-to-head card

LIVE

Black Forest Labs

FLUX.2 [flex]

Elo n/a

LiveBench—

SWE-bench—

Speed—

Output cost—

Llama 3.1 70B

Elo 1,240

LiveBench46.8%

SWE-bench40.2%

Speed125 tok/s

Output cost$0.4/1M

Frequently Asked Questions

Which is better overall, FLUX.2 [flex] or Llama 3.1 70B?: 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, FLUX.2 [flex] or Llama 3.1 70B?: 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, FLUX.2 [flex] or Llama 3.1 70B?: 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?: Llama 3.1 70B 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. FLUX.2 [flex] and Llama 3.1 70B Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Similar Head-to-Head Comparisons

All FLUX.2 [flex] matchups →|All Llama 3.1 70B matchups →

FLUX.2 [flex] vs FLUX.1.1 [pro] (previous flux)FLUX.2 [flex] vs FLUX.2 [max] (next flux)Llama 3.1 70B vs Llama 3.1 405B (previous llama)Llama 3.1 70B vs Llama 3.3 70B (next llama)Llama 4 Maverick vs Llama 3.1 70B Llama 4 Scout vs Llama 3.1 70B

Benchmark

FLUX.2 [flex]

Llama 3.1 70B

Advantage Delta

Image Elo

1,224

seed-bootstrap · Aug 1, 2026

—

Generation time

2.8s

seed-bootstrap · Aug 1, 2026

—

Price per 1k images

$60/1k

seed-bootstrap · Aug 1, 2026

—

Prompt adherence

90.5%

seed-bootstrap · Aug 1, 2026

—

Text rendering

91.5%

seed-bootstrap · Aug 1, 2026

—

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.2 [flex]

FLUX.2 [flex] 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.2 [flex]	FLUX.2 [flex] is the side marked multimodal in the catalog.

Frequently Asked Questions

Which is better overall, FLUX.2 [flex] or Llama 3.1 70B?

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, FLUX.2 [flex] or Llama 3.1 70B?

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, FLUX.2 [flex] or Llama 3.1 70B?

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?

Llama 3.1 70B 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. FLUX.2 [flex] and Llama 3.1 70B Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.