LLM Comparison

GPT-5.6 Terra vs Qwen3.8 Flash Next: benchmark scores, pricing & comparison.

Side-by-side GPT-5.6 Terra vs Qwen3.8 Flash Next 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.

Rank #13 vs #19AskClash overall scores 65.7 vs 57.6.
Pricing $2.50/$15.0 vs $0.16/$0.47Input and output token prices per 1M tokens when published.
Proprietary vs Open WeightOpenAI vs Alibaba.

GPT-5.6 Terra vs Qwen3.8 Flash Next benchmark comparison

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

MetricGPT-5.6 TerraQwen3.8 Flash Next
Overall Score65.757.6
Leaderboard Rank#13#19
ACB56.466.5
RWT8.5
Coding Agent Index77.0
HLE35.9
GPQA92.991.7
IFEval81.3
SWE-Pro63.462.5
SWE-Atlas81.0
Terminal-Bench87.4
DeepSWE69.658.7
GDPval-AA1593.01743.0
Finance Agent54.4
CharXiv90.6
MMMU-Pro80.7
ARC-AGI 283.9
Tau286.3
MRCR89.6
Input Price (per 1M tokens)$2.50$0.16
Output Price (per 1M tokens)$15.0$0.47
Context Window1M1M
Benchmarks Published149

GPT-5.6 Terra vs Qwen3.8 Flash Next head-to-head charts

GPT-5.6 Terra leads 4 and Qwen3.8 Flash Next leads 2 of 6 shared benchmarks. Qwen3.8 Flash Next is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

GPT-5.6 TerraQwen3.8 Flash Next
Overall
65.7GPT-5.6 Terra
57.6Qwen3.8 Flash Next
ACB
56.4GPT-5.6 Terra
66.5Qwen3.8 Flash Next
GPQA
92.9GPT-5.6 Terra
91.7Qwen3.8 Flash Next
SWE-Pro
63.4GPT-5.6 Terra
62.5Qwen3.8 Flash Next
DeepSWE
69.6GPT-5.6 Terra
58.7Qwen3.8 Flash Next
GDPval-AA
1593.0GPT-5.6 Terra
1743.0Qwen3.8 Flash Next
GPT-5.6 Terra
Input$2.50
Output$15.0
Workload$5.50
Context1M
Qwen3.8 Flash Next
Input$0.16
Output$0.47
Workload$0.25
Context1M

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

More GPT-5.6 Terra and Qwen3.8 Flash Next comparisons

Explore how GPT-5.6 Terra and Qwen3.8 Flash Next stack up against other top-ranked LLMs.

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.