How do DeepSeek V4 Flash Vision Exp and GPT-5.6 Luna compare on coding benchmarks?

The comparison table shows SWE-bench, SWE-Pro, SWE-Atlas, Terminal-Bench, DeepSWE, and coding agent index scores for both DeepSeek V4 Flash Vision Exp and GPT-5.6 Luna when publicly disclosed.

LLM Comparison

DeepSeek V4 Flash Vision Exp vs GPT-5.6 Luna: benchmark scores, pricing & comparison.

Q: Which is better: DeepSeek V4 Flash Vision Exp or GPT-5.6 Luna?

AskClash compares DeepSeek V4 Flash Vision Exp and GPT-5.6 Luna side by side across SWE-bench, GPQA, HLE, Terminal-Bench, coding agent scores, token pricing, AskClash ACB, and context window so you can see which model wins on each benchmark.

Side-by-side DeepSeek V4 Flash Vision Exp vs GPT-5.6 Luna comparison across SWE-bench, GPQA, HLE, Terminal-Bench, coding agent scores, token pricing, context window, and AskClash RWT. Green marks the winner on each benchmark.

Open live leaderboard DeepSeek V4 Flash Vision Exp model page GPT-5.6 Luna model page

Rank #21 vs #22AskClash overall scores 54.6 vs 54.3.

Pricing $0.14/$0.28 vs $1.00/$6.00Input and output token prices per 1M tokens when published.

API vs ProprietaryDeepSeek vs OpenAI.

DeepSeek V4 Flash Vision Exp vs GPT-5.6 Luna benchmark comparison

Green cells highlight the winning model for each metric. Scores are cached from the AskClash LLM leaderboard snapshot.

Metric	DeepSeek V4 Flash Vision Exp	GPT-5.6 Luna
Overall Score	54.6	54.3
Leaderboard Rank	#21	#22
ACB	58.6	56.1
RWT	—	9.5
Coding Agent Index	—	75.0
GPQA	—	92.3
SWE-Pro	—	62.7
SWE-Atlas	—	81.0
Terminal-Bench	83.9	84.7
DeepSWE	59.3	67.2
GDPval-AA	—	1592.0
Finance Agent	—	55.0
MMMU-Pro	—	78.4
ARC-AGI 2	—	59.5
MRCR	—	41.3
Input Price (per 1M tokens)	$0.14	$1.00
Output Price (per 1M tokens)	$0.28	$6.00
Context Window	1M	1M
Benchmarks Published	3	13

DeepSeek V4 Flash Vision Exp vs GPT-5.6 Luna head-to-head charts

DeepSeek V4 Flash Vision Exp leads 2 and GPT-5.6 Luna leads 2 of 4 shared benchmarks. DeepSeek V4 Flash Vision Exp is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

DeepSeek V4 Flash Vision ExpGPT-5.6 Luna

Overall

54.6DeepSeek V4 Flash Vision Exp

54.3GPT-5.6 Luna

ACB

58.6DeepSeek V4 Flash Vision Exp

56.1GPT-5.6 Luna

Terminal-Bench

83.9DeepSeek V4 Flash Vision Exp

84.7GPT-5.6 Luna

DeepSWE

59.3DeepSeek V4 Flash Vision Exp

67.2GPT-5.6 Luna

DeepSeek V4 Flash Vision Exp

Input$0.14

Output$0.28

Workload$0.20

Context1M

GPT-5.6 Luna

Input$1.00

Output$6.00

Workload$2.20

Context1M

Workload = published cost of 1M input + 200K output tokens. Open the live leaderboard for interactive compare charts.

More DeepSeek V4 Flash Vision Exp and GPT-5.6 Luna comparisons

Explore how DeepSeek V4 Flash Vision Exp and GPT-5.6 Luna stack up against other top-ranked LLMs.

Claude Fable 5.1 vs DeepSeek V4 Flash Vision Exp Claude Fable 5.1 vs GPT-5.6 Luna Claude Fable 5 vs DeepSeek V4 Flash Vision Exp Claude Fable 5 vs GPT-5.6 Luna GPT-6 Astra vs DeepSeek V4 Flash Vision Exp GPT-6 Astra vs GPT-5.6 Luna GPT-5.6 Sol vs DeepSeek V4 Flash Vision Exp GPT-5.6 Sol vs GPT-5.6 Luna Claude Opus 5 vs DeepSeek V4 Flash Vision Exp Claude Opus 5 vs GPT-5.6 Luna

How to read this comparison

Benchmark scores

Higher is better for all benchmark scores (SWE-bench, GPQA, HLE, Terminal-Bench, etc.). Green marks the model with the higher score.

Token pricing

Lower is better for input and output prices. Green marks the cheaper model per 1M tokens.

Coverage matters

Models with fewer disclosed benchmark cells may have inflated percentile scores. Check the benchmark cell count for context.

This comparison page is generated from the AskClash LLM leaderboard cache. Open the live leaderboard for real-time scores and interactive filtering.