Benchmark profile
Flame-VLM-Code
A vision-language coding benchmark for generating correct code from visual and multimodal inputs.
Data verifiedHow BenchLM shows Flame-VLM-Code right now
BenchLM is tracking Flame-VLM-Code in the local dataset, but exact-source verification records for these rows are still being attached. To avoid a blank benchmark page, BenchLM shows the current tracked rows below as a display-only reference table.
These tracked rows are useful for inspection and spot-checking, but until exact-source attachments are completed they should not be treated as fully verified public benchmark rows.
Tracked score on Flame-VLM-Code — July 23, 2026
BenchLM mirrors the published tracked score view for Flame-VLM-Code. Claude Opus 4.6 leads the public snapshot at 98.8% , followed by GLM-5V-Turbo (93.8%) and Kimi K2.5 (88.8%). BenchLM does not use these results to rank models overall.
Claude Opus 4.6
Anthropic
claude-opus-4-6
GLM-5V-Turbo
Z.AI
glm-5v-turbo
Kimi K2.5
Moonshot AI
kimi-k2-5
Tracked score table (3 models)
ScoreThe published Flame-VLM-Code snapshot places Claude Opus 4.6 first at 98.8%. The third row is 10.0 points behind. The broader top-10 range is 10.0 points, so the table still separates the published systems.
3 models have been evaluated on Flame-VLM-Code. The benchmark falls in the Multimodal & Grounded category. This category carries a 12% weight in BenchLM.ai's overall scoring system. Flame-VLM-Code is currently displayed for reference but excluded from the scoring formula, so it does not directly affect overall rankings.
About Flame-VLM-Code
Year
2026
Tasks
Multimodal coding tasks
Format
Vision-language code generation
Difficulty
Multimodal coding
BenchLM tracks Flame-VLM-Code as a display-only multimodal coding benchmark reference.
BenchLM freshness & provenance
Version
Flame-VLM-Code 2026
Refresh cadence
Quarterly
Staleness state
Current
Question availability
Public benchmark set
BenchLM uses freshness metadata to decide whether a benchmark should still be treated as a strong differentiator, a benchmark to watch, or a display-only reference. For the full scoring policy, see the BenchLM methodology page.
FAQ
What does Flame-VLM-Code measure?
A vision-language coding benchmark for generating correct code from visual and multimodal inputs.
Which model leads the published Flame-VLM-Code snapshot?
Claude Opus 4.6 currently leads the published Flame-VLM-Code snapshot with 98.8% tracked score. BenchLM shows this benchmark for display only and does not use it in overall rankings.
How many models are evaluated on Flame-VLM-Code?
3 AI models are included in BenchLM's mirrored Flame-VLM-Code snapshot, based on the public leaderboard captured on July 23, 2026.
Choose a model with this week’s evidence
Join 2,000+ readers for ranking moves, pricing changes, and the claims that still need proof.
One email each week. Unsubscribe anytime.