reasoning benchmark
FullStackBench zh Leaderboard
Chinese subset of FullStackBench for evaluating end-to-end software engineering and full-stack development capability.
Updated Aug 17, 2026
Models3
Model coverage3
MetricScore
EvidenceB
FullStackBench zh Ranking
Higher score ranks better on this benchmark.
Sort by
Rank | Model | Score | Percentile | Participants | Evidence | Evaluated |
|---|
| Rank01 | ModelAC | Score58.7% | Percentile100.0% | Participants3 | EvidenceC | Evaluated |
| Rank02 | ModelAC | Score57.4% | Percentile50.0% | Participants3 | EvidenceC | Evaluated |
| Rank03 | ModelAC | Score55.0% | Percentile0.0% | Participants3 | EvidenceC | Evaluated |
FullStackBench zh Highlights
The leading models and scores on this benchmark.
FullStackBench zh Score Distribution
A closer view of the leading scores on this benchmark.
The Top AI Models for FullStackBench zh
The first five results on this benchmark, with official price and output speed added where the model identity can be matched.
Ranking basisThis fullstackbench zh AI model leaderboard uses descending score in the benchmark's original unit. The leaderboard ranking keeps matched price and speed data separate from benchmark evidence.
- 01ACQwen3.5-122B-A10BAlibaba Cloud / Qwen Team
- Score
- 58.7%
- Price
- $0.40 input / $3.2 output per 1M tokens
Strengths
- Ranks #1 of 3 compared models
- 100th percentile on this benchmark
- C evidence result
Considerations
- This result measures FullStackBench zh, not total model capability
- 02ACQwen3.5-27BAlibaba Cloud / Qwen Team
- Score
- 57.4%
- Price
- $0.30 input / $2.4 output per 1M tokens
- Speed
- Up to 6.7 tok/s via Novita
Strengths
- Ranks #2 of 3 compared models
- 50th percentile on this benchmark
- C evidence result
Considerations
- This result measures FullStackBench zh, not total model capability
- 03ACQwen3.5-35B-A3BAlibaba Cloud / Qwen Team
- Score
- 55.0%
- Price
- $0.25 input / $2.0 output per 1M tokens
Strengths
- Ranks #3 of 3 compared models
- 0th percentile on this benchmark
- C evidence result
Considerations
- This result measures FullStackBench zh, not total model capability
Selection summary
Best AI Models for FullStackBench zh
Qwen3.5-122B-A10B currently leads FullStackBench zh with 58.7%. It is the top model on this specific benchmark, while the best LLM for the broader task should also be checked against other benchmarks, price and runtime.
Use this leaderboard with the supporting benchmark results and coverage details above. A leaderboard position summarizes the selected ranking signal; it does not replace workload-specific testing.
What is FullStackBench zh?
What FullStackBench zh measures and how its scores work.
Chinese subset of FullStackBench for evaluating end-to-end software engineering and full-stack development capability.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
- Family
- FullStackBench zh
- Modality
- text
- Primary category
- reasoning
- Score direction
- higher
- LLMBoard eligible
- Yes
- Evaluation key
- fullstackbench-zh|llm-stats-current
Benchmark scores retain their original unit. Overall score eligibility is shown separately.
FAQ
Common questions about FullStackBench zh.
Which model scores highest on FullStackBench zh?
Qwen3.5-122B-A10B is currently ranked first with 58.7%.
What does FullStackBench zh measure?
Chinese subset of FullStackBench for evaluating end-to-end software engineering and full-stack development capability.
Is a higher score better?
Yes. Higher values rank better for this benchmark.
How many models are compared?
3 model results are currently shown.
Does this benchmark affect the overall score?
Yes. This benchmark can contribute to the current LLMBoard capability score.