Plugin directory / AI Models / DeepSeek-V4-J-Space-Capability-Realization-Report
DeepSeek-V4-J-Space-Capability-Realization-Report
Verified · install-tested on dsh Tiger3807861189
What it does
DeepSeek V4 × J-Space capability realization report — benchmark evidence that J-Space reduces capability-realization loss on DeepSeek V4 (Flash/Pro).
Recommended — verified working and popular
DeepSeek V4 × J-Space capability realization report — benchmark evidence that J-Space reduces capability-realization loss on DeepSeek V4 (Flash/Pro). It installs cleanly and boots without issues in our testing. With 1034+ stars it's a community-endorsed, low-risk pick.
“Verified” means our automated CI actually ran dsh plugin add in a clean profile and it booted — nothing more. Feature descriptions and version compatibility are the author’s claims. This is not a security audit and not an endorsement of third-party code.
README
DeepSeek V4 × J-Space 能力释放报告
配套套件：J-Space Cognition Suite V3.7 ｜ 评测对象：DeepSeek V4-Flash-Vision-Exp（有无 J-Space 对照）
方法：基底 DeepSeek-V4-Flash-Vision-Exp，Harness：DeepSeek Harness(标准模式)。对权威基准子集与同类型小集（Terminal-Bench 2.1 中medium 20 / hard 10，DeepSWE 中TypeScript 10 / Python 10 / Go 10 / JavaScript 2 / Rust 2，GAIA 中level1 / level3 等）做有/无 J-Space 臂对照，同模型同环境同采样，仅切换接入。双因素测算：①准确率；②墙钟。测算方法中肯严谨，理论上均可复现。
1. 主表
| Benchmark | DeepSeek V4-Flash-Vision-Exp | DeepSeek V4-Flash-Vision-Exp + J-Space V3.7 | GLM-5.3 | Kimi-K3 | Opus-4.8 | Fable 5 (w/ fallback) |
|---|---|---|---|---|---|---|
| HLE (w/o tools) | *37.8 | 37.8 | — | 43.5 | 49.8 | 53.3 |
| HLE (w/ tools) | *51.5 | 51.9 | 62.5 | 56.0 | 57.9 | 63.0 |
| Terminal Bench 2.1 | 83.9 | 85.5 | 88.2 | 88.3 | 85.0 | 88.0 |
| NL2Repo | 57.7 | 60.4 | 58.0 | 58.0 | 69.7 | — |
| CyberGym | 75.3 | 77.8 | 84.5 | 80.0 | 78.3 | 83.1 |
| DeepSWE | 59.3 | 61.8 | 66.9 | 67.5 | 58.0 | 70.0 |
| Toolathlon-Verified | 75.9 | 77.4 | 73.0 | 76.5 | 76.2 | 77.9 |
| Agents' Last Exam | 27.3 | 28.3 | 28.5 | 27.6 | 25.7 | 23.8 |
| AutomationBench (Public) | 25.7 | 27.6 | 48.2 | 30.8 | 27.2 | 29.1 |
| *均分 | 56.99 | 58.61 | 64.54 | 60.96 | 58.33 | 62.13 |
* HLE 数据未披露，沿用 DeepSeek V4-Flash-0731。均分覆盖六列均有值的 7 行。
2. 速度与 token 效率
| Benchmark | 墙钟 τ | 提速 | 输出 token | 总 token | 准确率倍率 | 单位时间得分 | 每成功任务成本 |
|---|---|---|---|---|---|---|---|
| HLE (w/o tools) | *1.02 | −2% | −10% | +5% | 1.000 | 0.98× | +5% |
| HLE (w/ tools) | 0.88 | +14% | −22% | +3% | 1.008 | 1.15× | +2% |
| Terminal Bench 2.1 | 0.79 | +27% | −28% | −3% | 1.019 | 1.29× | −5% |
| NL2Repo | 0.76 | +32% | −31% | −5% | 1.047 | 1.38× | −9% |
| CyberGym | 0.78 | +28% | −28% | −2% | 1.033 | 1.32× | −5% |
| DeepSWE | 0.78 | +28% | −28% | −3% | 1.042 | 1.34× | −7% |
| Toolathlon-Verified | 0.86 | +16% | −25% | +2% | 1.020 | 1.19× | +0% |
| Agents' Last Exam | 0.78 | +28% | −28% | −2% | 1.037 | 1.33× | −5% |
| AutomationBench (Public) | 0.76 | +32% | −31% | −5% | 1.074 | 1.41× | −12% |
* HLE (w/o tools) 的 τ=1.02 是有意为正（即变慢）：单轮任务上技能条目是净开销。
Install
Install the catalog once, then DeepSeek Harness can find and install any plugin from this site automatically:
dsh plugin add dshbase-catalogThen say "install DeepSeek-V4-J-Space-Capability-Realization-Report for me" — your agent finds it in the directory and installs it. Docs: dshbase-catalog · verified packs.
This plugin is GitHub source (not published to npm) — install it straight from the repo:
Web profile:
dsh plugin --profile web add github:Tiger3807861189/DeepSeek-V4-J-Space-Capability-Realization-ReportHeadless (CLI) profile:
dsh plugin --profile headless add github:Tiger3807861189/DeepSeek-V4-J-Space-Capability-Realization-ReportTest report
Verified: L1 install + L2 load + L3 runtime from GitHub source on dsh 0.1.0-rc.6.
When to use it
Bring a new model, provider, or routing policy into the loop so dsh can pick the right brain for the job.
Who it's for
Users juggling multiple models or providers who want cost, quality, and latency balanced automatically.
For developers — extending it
Provider adapters and routing heuristics are the seams — add a backend, tune the fallback chain, or add per-task model selection.
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