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SkillsBench (Vals AI) leaderboard

DeepSeek V4.1 Flash leads
69.8%
models measured
34
lead over #2
+3.8 pts
median
52.2%

Leader on SkillsBench (Vals AI) · read October 22

skillsbench_vals_ai.py


        # SkillsBench (Vals AI), read October 22
        leaders = {
            "DeepSeek V4.1 Flash": 69.8%,    "Grok 4.5": 66.0%,    "Gemini 3.7 Flash": 65.9%,
        }
      

On October 22, 2026, 34 of our catalog's models had a SkillsBench (Vals AI) result, and DeepSeek V4.1 Flash led with 69.8%, ahead of SpaceXAI Grok 4.5 at 66.0%.

Coding agents given task-specific skills, all run in one agent harness. The score as Vals AI publishes it.

Role in the index

A coding board we show beside the Vibe Coding Index, not inside it: the index keeps the six boards it was defined on, so a score does not move every time a board is added. Read the methodology

34 models with a result

Original board: Vals AI boards
SkillsBench (Vals AI) results for models in the catalog
# Model Result Cost per test Duration, as printed Evidence Coding index Output $/Mtok
1 DeepSeek V4.1 FlashDeepSeek 69.8% $0.09 3m 43s 62.5 $0.84
2 Grok 4.5xAI 66.0% $0.58 2m 16s 58.6 $6.00
3 Gemini 3.7 FlashGoogle 65.9% $1.80 3m 06s 58.0 $3.75
4 GPT-5.5OpenAI 62.5% $1.57 4m 40s 71.3 $30.00
5 Claude Fable 5.1Anthropic 61.5% $4.52 11m 02s 84.2 $50.00
6 GPT-5.6 LunaOpenAI 60.5% $0.21 5m 20s 58.0 $1.20
7 Claude Opus 5Anthropic 60.4% $2.51 8m 25s 83.0 $25.00
8 Claude Opus 4.8Anthropic 59.2% $4.77 15m 30s 65.0 $25.00
9 Muse Spark 1.1Meta 59.2% $0.45 6m 16s 70.3 $4.25
10 GPT-5.6 TerraOpenAI 58.9% $1.75 6m 55s 63.9 $12.00
11 Gemini 3.8 FlashGoogle 58.0% $2.34 3m 55s 61.6 $3.75
12 Grok 4.6xAI 55.8% $0.92 13m 28s 65.7 $6.00
13 Qwen3.7 PlusQwen 54.3% $0.14 12m 04s 33.2 $1.28
14 GPT-5.6 SolOpenAI 54.1% $4.14 13m 07s 73.5 $20.00
15 DeepSeek V4 Pro 0813DeepSeek 53.8% $0.37 11m 15s 56.1 $1.98
16 Muse Spark 1.2Meta 53.0% $0.65 13m 00s 55.7 $4.25
17 Gemini 3.5 FlashGoogle 52.7% $1.25 7m 15s 39.8 $9.00
18 GPT-5.4OpenAI 51.7% $2.04 9m 02s 64.4 $15.00
19 MiniMax M3MiniMax 51.5% $0.50 15m 28s 39.2 $1.20
20 DeepSeek V4 Pro 0423DeepSeek 51.3% $0.40 8m 16s 38.7 $2.976
21 DeepSeek V4 Flash 0731DeepSeek 50.7% $0.13 6m 52s 51.8 $0.396
22 Kimi K2.7 CodeMoonshot AI 50.0% $0.44 13m 24s 53.4 $4.00
23 Claude Sonnet 4.6Anthropic 49.0% $1.38 14m 20s 57.3 $15.00
24 GLM 5.3Z.ai 47.5% $0.71 13m 07s 70.6 $4.40
25 Claude Sonnet 5Anthropic 46.5% $2.90 15m 12s 57.7 $10.00
26 GLM 5.2Z.ai 45.1% $0.81 19m 52s 61.1 $4.40
27 Qwen3.8 Max (0902)Qwen 42.0% $0.52 15m 48s 62.4 $6.00
28 Grok 4.3xAI 40.6% $0.42 4m 37s 37.4 $2.50
29 GLM 5.3 FlashZ.ai 40.2% $0.04 12m 09s 57.7 $0.50
30 Qwen3.8 27BQwen 38.1% $0.82 6m 41s 74.2 $2.55
31 T Inkling SmallThinking Machines 33.6% $0.15 11m 41s 27.3 $1.20
32 Ling 3.0 FlashinclusionAI 27.9% $0.06 4m 52s 29.6 $0.1215
33 T InklingThinking Machines 26.1% $0.83 15m 39s 31.5 $4.05
34 Mercury 2.5Inception 18.1% $0.10 49 s 1.6 $0.15

Only models in our catalog are listed, and each appears once with its best published run. 137 rows were read from the source on October 22, 2026, and rows that match no catalog model are left out. Cost per test is what Vals AI reports one test cost on the run behind the result, in US dollars. Every other column is a figure the board publishes for the same run.