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Comparison

Ox Alpha vs GPT-5

Head-to-head on an independent benchmark of 10 real-world coding tasks: the stealth model against OpenAI's GPT-5.6 (sol), max effort.

80%
Ox Alpha
ox-alpha · 8/10 tasks
VS
52%
GPT-5
gpt-5.6-sol [max] · mean pass rate
Task by task

Where each model wins.

7
tasks where Ox Alpha had the edge
2
tasks where GPT-5 had the edge
1
tasks both solved cleanly
0
tasks neither solved
Taskgpt-5.6-sol [max]ox-alphaVerdict
anko-typed-variable-bindings 2/4 Ox Alpha
arktype-json-schema-refs 3/4 Ox Alpha
fastapi-deprecation-headers 3/4 Ox Alpha
helm-unified-manifest-stream 4/4 Both solved
igel-persist-feature-schema 0/4 Ox Alpha
katex-multicolumn-array-spans 3/4 Ox Alpha
meriyah-explicit-resource-decl 0/4 Ox Alpha
query-persist-restored-state 1/4 Ox Alpha
scc-bounded-memory-spilling 4/4 GPT-5
vulture-persistent-analysis-cache 1/4 GPT-5
Mean on these 10 52% 80%

Independent community benchmark — 10 real-world coding tasks. Reference models were scored as passes out of 4 attempts per task; Ox Alpha was recorded as pass/fail. "Edge" = Ox Alpha passed while GPT-5 missed at least one attempt, or vice-versa. Third-party data presented as published — 10 tasks is a small sample, so read it as directional.

What the numbers say

Ox Alpha vs GPT-5.6 (sol), max effort
  • 8 of 10 solved by Ox Alpha, versus 2 tasks that GPT-5 passed on all four attempts.
  • Solved where GPT-5 went 0/4: igel-persist-feature-schema, meriyah-explicit-resource-decl.
  • GPT-5's strongest ground: 2 tasks it passed that Ox Alpha missed — scc-bounded-memory-spilling, vulture-persistent-analysis-cache.
  • Both stumbled on 0 tasks — a reminder that no model is a guaranteed pass on real-world bugs.

Ox Alpha at a glance

What's known about the stealth model
Type
Reasoning model
Context window
1,048,576 tokens
Max output
131,072 tokens
Inputs
Text · Image · Video
Developer features
Tool calling · JSON output
Creator
Unknown (stealth)

About GPT-5

OpenAI · benchmarked build: gpt-5.6-sol [max]
  • OpenAI's GPT-5.6 "sol" build, run at maximum reasoning effort.
  • Mean pass rate on these 10 tasks: 52% — passing at least one attempt on 8 of 10.

Why it matters

Reading a 10-task benchmark honestly
  • These are real repository tasks, not toy puzzles — the kind of work a reasoning model is built for.
  • Ten tasks is a small sample; a few tasks either way would move the means. Use it to decide what to try, not to declare a winner.
  • The best benchmark is your own problem. Ox Alpha is free to try right now.

Run your own benchmark.

Paste the bug, the spec, or the whole repo. Ox Alpha is free while it's in stealth.

Try Ox Alpha