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

Mistral: Codestral 2508 vs FLUX.2 [max] benchmark

Name: Mistral: Codestral 2508 vs FLUX.2 [max] AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

Comparing verified benchmark accuracy, speed, and token pricing between Mistral: Codestral 2508 and FLUX.2 [max]. Review the complete breakdown below to determine which model best fits your performance and budget requirements.

Share Analysis:

Mistral

Mistral: Codestral 2508

Auto-discovered from OpenRouter (mistralai/codestral-2508). Preview until a second source matches.

Black Forest Labs

FLUX.2 [max]

Black Forest Labs maximum-capacity flow-matching model with photoreal anatomy and leading typography fidelity.

Img Elo 1,233$70/1k imgs

Top Rival Showdowns for Mistral: Codestral 2508

All Matchups

Compare vs:vs GPT Image 2 (High)vs Reve 2.1 vs Nano Banana Pro (Gemini 3 Pro Image)vs FLUX.2 [flex]vs Ideogram 4.0 (Quality)

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.

Mistral: Codestral 2508 (0)vsFLUX.2 [max] (5)

Mistral: Codestral 2508: 0W (0%)Overall: FLUX.2 [max]FLUX.2 [max]: 5W (100%)

← Mistral: Codestral 2508FLUX.2 [max] →

🏆FLUX.2 [max](3/3)

Visual Quality & Adherence

Arena Preference Elo, prompt fidelity & typography score

Benchmark

Mistral: Codestral 2508vsFLUX.2 [max]

Image Elo

—vs1,233

Prompt adherence

—vs91.2%

Text rendering

—vs92.8%

Mistral: Codestral 2508: 0WFLUX.2 [max]: 3W

🏆FLUX.2 [max](1/1)

Generation Latency

Time to render full-resolution image snapshot (seconds)

Benchmark

Mistral: Codestral 2508vsFLUX.2 [max]

Generation time

—vs5.1s

Mistral: Codestral 2508: 0WFLUX.2 [max]: 1W

🏆FLUX.2 [max](1/1)

Cost Efficiency

API inference cost per 1,000 generated images

Benchmark

Mistral: Codestral 2508vsFLUX.2 [max]

Price per 1k images

—vs$70/1k

Mistral: Codestral 2508: 0WFLUX.2 [max]: 1W

Side-by-Side Benchmark Matrix

Image Elo

Mistral: Codestral 2508—

FLUX.2 [max]1,233

seed-bootstrap · Aug 1, 2026

Generation time

Mistral: Codestral 2508—

FLUX.2 [max]5.1s

seed-bootstrap · Aug 1, 2026

Price per 1k images

Mistral: Codestral 2508—

FLUX.2 [max]$70/1k

seed-bootstrap · Aug 1, 2026

Prompt adherence

Mistral: Codestral 2508—

FLUX.2 [max]91.2%

seed-bootstrap · Aug 1, 2026

Text rendering

Mistral: Codestral 2508—

FLUX.2 [max]92.8%

seed-bootstrap · Aug 1, 2026

Benchmark	Mistral: Codestral 2508	FLUX.2 [max]	Advantage Delta
Image Elo	—	1,233 seed-bootstrap · Aug 1, 2026	—
Generation time	—	5.1s seed-bootstrap · Aug 1, 2026	—
Price per 1k images	—	$70/1k seed-bootstrap · Aug 1, 2026	—
Prompt adherence	—	91.2% seed-bootstrap · Aug 1, 2026	—
Text rendering	—	92.8% 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 Mistral: Codestral 2508

Monthly Image Production Volume25k images / month (25000 imgs)

Quick Presets:

Mistral: Codestral 2508$0.00 / mo

Rate: $0/1k

FLUX.2 [max]$1,750.00 / mo

Rate: $70/1k

Estimated Cost Delta

Mistral: Codestral 2508 is estimated to save $1,750.00/month ($21,000/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 [max]

FLUX.2 [max] 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 [max]	FLUX.2 [max] 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!

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CompareLLM AI Matrix

Verified Head-to-Head Telemetry

LIVE BENCHMARK

Mistral

Mistral: Codestral 2508

Elo n/a

SWE-bench—

Speed (tok/s)256k

Input / 1M Tokens$0.3/1M

Output / 1M Tokens$0.9/1M

Black Forest Labs

FLUX.2 [max]

Elo n/a

SWE-bench—

Speed (tok/s)—

Input / 1M Tokens$70/1k

Output / 1M Tokens$70/1k

Frequently Asked Questions

Which is better overall, Mistral: Codestral 2508 or FLUX.2 [max]?: 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, Mistral: Codestral 2508 or FLUX.2 [max]?: 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, Mistral: Codestral 2508 or FLUX.2 [max]?: 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?: 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. Mistral: Codestral 2508 and FLUX.2 [max] Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Similar Head-to-Head Comparisons

All Mistral: Codestral 2508 matchups →|All FLUX.2 [max] matchups →

FLUX.2 [max] vs FLUX.2 [flex] (previous flux)FLUX.1.1 [pro] vs FLUX.2 [max]GPT Image 2 (High) vs FLUX.2 [max]Reve 2.1 vs FLUX.2 [max]Nano Banana Pro (Gemini 3 Pro Image) vs FLUX.2 [max]Nano Banana 2 (Gemini 3.1 Flash Image) vs FLUX.2 [max]

Side-by-Side Benchmark Matrix

Image Elo

Mistral: Codestral 2508—

FLUX.2 [max]1,233

seed-bootstrap · Aug 1, 2026

Generation time

Mistral: Codestral 2508—

FLUX.2 [max]5.1s

seed-bootstrap · Aug 1, 2026

Price per 1k images

Mistral: Codestral 2508—

FLUX.2 [max]$70/1k

seed-bootstrap · Aug 1, 2026

Prompt adherence

Mistral: Codestral 2508—

FLUX.2 [max]91.2%

seed-bootstrap · Aug 1, 2026

Text rendering

Mistral: Codestral 2508—

FLUX.2 [max]92.8%

seed-bootstrap · Aug 1, 2026

Benchmark

Mistral: Codestral 2508

FLUX.2 [max]

Advantage Delta

Image Elo

—

1,233

seed-bootstrap · Aug 1, 2026

—

Generation time

—

5.1s

seed-bootstrap · Aug 1, 2026

—

Price per 1k images

—

$70/1k

seed-bootstrap · Aug 1, 2026

—

Prompt adherence

—

91.2%

seed-bootstrap · Aug 1, 2026

—

Text rendering

—

92.8%

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 [max]

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

Frequently Asked Questions

Which is better overall, Mistral: Codestral 2508 or FLUX.2 [max]?

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, Mistral: Codestral 2508 or FLUX.2 [max]?

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, Mistral: Codestral 2508 or FLUX.2 [max]?

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?

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. Mistral: Codestral 2508 and FLUX.2 [max] Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.