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

FLUX.1.1 [pro] vs Z.ai: GLM 5V Turbo benchmark

Name: FLUX.1.1 [pro] vs Z.ai: GLM 5V Turbo AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

This page compares FLUX.1.1 [pro] (Black Forest Labs) and Z.ai: GLM 5V Turbo (Zhipu) 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.

Share Analysis:

WhatsApp Telegram X / Post LinkedIn Reddit

Black Forest Labs

FLUX.1.1 [pro]

First-generation professional API model from Black Forest Labs, renowned for 6x faster generation than original FLUX.1 Pro.

Zhipu

Z.ai: GLM 5V Turbo

Auto-discovered from OpenRouter (z-ai/glm-5v-turbo). Preview until a second source matches.

Elo 1,475$4/1M out

Swap or Add Any Model to this Matchup

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.

FLUX.1.1 [pro] (0)vsZ.ai: GLM 5V Turbo (10)

FLUX.1.1 [pro]: 0W (0%)Overall: Z.ai: GLM 5V TurboZ.ai: GLM 5V Turbo: 10W (100%)

← FLUX.1.1 [pro]Z.ai: GLM 5V Turbo →

Z.ai: GLM 5V Turbo (5/5)

Intelligence & Reasoning

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

Preference Elo

—vs1,475

Coding Elo

—vs1,482

SWE-bench

—vs65.2%

LiveBench

—vs63.8%

GPQA Diamond

—vs77.4%

FLUX.1.1 [pro]: 0WZ.ai: GLM 5V Turbo: 5W

Z.ai: GLM 5V Turbo (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

—vs112 tok/s

Time to first token

—vs180 ms

FLUX.1.1 [pro]: 0WZ.ai: GLM 5V Turbo: 2W

Z.ai: GLM 5V Turbo (3/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

—vs$4/1M

Input price

—vs$1.2/1M

Context window

—vs203k

FLUX.1.1 [pro]: 0WZ.ai: GLM 5V Turbo: 3W

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.1.1 [pro] 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

—

EloHigh is better

1,475

Code Elo

High is better

—

Code EloHigh is better

1,482

LiveBench

High is better

—

LiveBenchHigh is better

63.8%

SWE-bench

High is better

—

SWE-benchHigh is better

65.2%

GPQA

High is better

—

GPQAHigh is better

77.4%

TTFT

Low is better

—

TTFTLow is better

180 ms

Speed

High is better

—

SpeedHigh is better

112 tok/s

In $

Low is better

—

In $Low is better

$1.2/1M

Out $

Low is better

—

Out $Low is better

$4/1M

Context

High is better

—

ContextHigh is better

203k

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 / visioninsufficient data

Both accept images. Defaulting to the higher-Elo side (undefined).

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	insufficient data	Both accept images. Defaulting to the higher-Elo side (undefined).

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-1-1-pro-vs-glm-5v-turbo/opengraph-image for crawlers.

PNG

CompareLLM Matrix

Verified head-to-head card

LIVE

Black Forest Labs

FLUX.1.1 [pro]

Elo n/a

LiveBench—

SWE-bench—

Speed—

Output cost—

Zhipu

Z.ai: GLM 5V Turbo

Elo 1,475

LiveBench63.8%

SWE-bench65.2%

Speed112 tok/s

Output cost$4/1M

Frequently Asked Questions

Which is better overall, FLUX.1.1 [pro] or Z.ai: GLM 5V Turbo?: 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.1.1 [pro] or Z.ai: GLM 5V Turbo?: 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.1.1 [pro] or Z.ai: GLM 5V Turbo?: 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. FLUX.1.1 [pro] and Z.ai: GLM 5V Turbo Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Similar Head-to-Head Comparisons

All FLUX.1.1 [pro] matchups →|All Z.ai: GLM 5V Turbo matchups →

FLUX.1.1 [pro] vs FLUX.1 [schnell] (previous flux)FLUX.1.1 [pro] vs FLUX.2 [flex] (next flux)Z.ai: GLM 5V Turbo vs GLM-5.2 (previous glm)Z.ai: GLM 5V Turbo vs GLM-5.3 (next glm)FLUX.2 [max] vs FLUX.1.1 [pro]Claude Opus 4.5 vs Z.ai: GLM 5V Turbo

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

FLUX.1.1 [pro] (0)vsZ.ai: GLM 5V Turbo (10)

FLUX.1.1 [pro]: 0W (0%)Overall: Z.ai: GLM 5V TurboZ.ai: GLM 5V Turbo: 10W (100%)

← FLUX.1.1 [pro]Z.ai: GLM 5V Turbo →

Z.ai: GLM 5V Turbo (5/5)

Intelligence & Reasoning

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

Preference Elo

—vs1,475

Coding Elo

—vs1,482

SWE-bench

—vs65.2%

LiveBench

—vs63.8%

GPQA Diamond

—vs77.4%

FLUX.1.1 [pro]: 0WZ.ai: GLM 5V Turbo: 5W

Z.ai: GLM 5V Turbo (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

—vs112 tok/s

Time to first token

—vs180 ms

FLUX.1.1 [pro]: 0WZ.ai: GLM 5V Turbo: 2W

Z.ai: GLM 5V Turbo (3/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

—vs$4/1M

Input price

—vs$1.2/1M

Context window

—vs203k

FLUX.1.1 [pro]: 0WZ.ai: GLM 5V Turbo: 3W

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 / visioninsufficient data

Both accept images. Defaulting to the higher-Elo side (undefined).

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	insufficient data	Both accept images. Defaulting to the higher-Elo side (undefined).

Frequently Asked Questions

Which is better overall, FLUX.1.1 [pro] or Z.ai: GLM 5V Turbo?

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.1.1 [pro] or Z.ai: GLM 5V Turbo?

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.1.1 [pro] or Z.ai: GLM 5V Turbo?

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. FLUX.1.1 [pro] and Z.ai: GLM 5V Turbo Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.