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AlibabaChina· released Feb 2026· open weights

Qwen3.5 35B-A3B

Provisional: 6 comparable tests so far. Ranked once it reaches 6 across 3 counting categories.

Alibaba, China. One of 19 models from this lab on the Index.

Third-party publishedLow confidence (thin coverage)

Snapshot September 8, 2026

OpenCharts Index

52.2

Provisional: not enough comparable tests or counting categories to rank yet · 6 comparable tests · 0 counting categories

Drop any single test and the Index lands between 42.1 and 62.3.

HARD SET

Needs more results (0 of 8 so far)

Distance to today's frontier on the hardest tests. Not a measure of intelligence.

What it's known for

Qwen3.5 35B-A3B, in 6 results.

Its widest gap is on CritPt, 98.2% behind the best published result. No comparable results yet in knowledge, agentic, multimodal and long context. Between 40% and 50% behind the best published results, on average.

Strongest category

No category counts yet: a category counts once it has more than one comparable test and the model has taken at least half of them. The scores it has are below.

Best single result

GPQA Diamond

Answer a PhD-level multiple-choice question in physics, chemistry or biology that a web search will not settle.

83.5%

82.6% of the best (95.8%), above chance · #58 of 78.

Expert-level science questions are the closest thing to asking a specialist colleague. A model that gets them right can check a technical claim instead of echoing it.

Where it trails

CritPt

Solve an unpublished research-level physics problem to a numeric or symbolic answer checked by an official server.

0.6%

98.2% behind the best published result (32.3%) · #68 of 78.

Research physics is far past textbook recall. Only a few models produce anything a physicist would accept.

Not measured yet

No comparable result yet in these 4 categories. A blank is a blank, never a zero, and it does not lower the Index.

  • Knowledge
  • Agentic
  • Multimodal
  • Long context

Covered, but not averaged into the Index:

  • Reasoning2 of 6 tests · needs 3 · mean 42.2
  • Coding2 of 7 tests · needs 4 · mean 27.7
  • Math1 of 5 tests · needs 3 · mean 70.0
  • Human preferencesingle-test category, shown beside the Index · 68.8
Every score, with its source

See it at work

What Qwen3.5 35B-A3B was asked to do, and how it did.

Every test it has taken, by category, with the kind of task it faced, who produced the number and where the result landed against the best published one. The examples are original and illustrative, never items from the datasets themselves.

Math · mean 70.0 across 1 comparable test · not counted toward the Index yet (fewer than half the category's tests)

Solve competition mathematics problems that have a single exact integer answer.

70.0%

70.0% of the best (100.0%)
#73 of 78 · n = 45

none

45 problems: one problem is 2.2 points, so gaps of a few points are within noise.

Source: Epoch AI (internal runs)

Every result is read against the best published one on its test: percent scores as a share of the best above chance, Arena ratings as the expected win rate against the board leader, open-ended values on a log scale. Sitting a harder exam never lowers a model. Every number links to the publisher that produced it.

Head to head

Qwen3.5 35B-A3B against whoever you pick.

Choose a rival. Every counted test both have taken appears side by side as a share of the best published result on that test, with the category means above. A win is a higher share; a gap under 2 points is a tie, because one item on a 45-problem exam is 2.2 points and publishers' own standard errors are of that order.

Qwen3.5 35B-A3B

provisional·Index 52.2C-

0 : 5

wins · 0 ties · 5 shared

GPT-6 Astra

#1·Index 99.0A+

GPT-6 Astra comes out ahead on 5 of the 5 tests both have taken.

Category means

  • Reasoning

    42.2
    99.6
  • Knowledge

    100.0
  • Coding

    27.7
    97.7
  • Math

    70.0
    99.8
  • Agentic

    98.5
  • Human preference

    68.8

Shared tests · biggest gaps first

Bars are distances to the best published result on each test (percent scores above chance, Arena ratings as win rate against the leader, open-ended values on a log scale). Raw values as the publishers report them.

Open GPT-6 Astra

Scores

Every test, every source

The best published run per benchmark, the raw value as the publisher reports it, who produced the number, how close it comes to the best published result on that test, and where the model sits among every model scored on it. Percent scores are read above chance, Arena ratings as a win rate against the board leader, open-ended values on a log scale. A test with too few models to compare against is shown but not counted.

Category means

  • Reasoning42.2 · 2/6
  • Knowledge
  • Coding27.7 · 2/7
  • Math70.0 · 1/5
  • Agentic
  • Multimodal
  • Human preferencebeside68.8 · 1/1
  • Long context

Mean · tests taken of the category's comparable tests. A faded category either rests on fewer than half of them or is a single-test category (marked “beside”), which is shown next to the Index and never averaged into it.

GPQA DiamondEpoch-runReasoning

83.5%

82.6% of the best (95.8%), above chance
25th percentile of 78 · n = 198

Source: Epoch AI — AI Benchmarking Hub
CritPtLeaderboardReasoning

0.6%

1.8% of the best (32.3%)
12th percentile of 78

none

Source: Epoch AI — AI Benchmarking Hub
SciCodeLeaderboardCoding

29.3%

47.2% of the best (62.0%)
1th percentile of 73 · n = 338

none

Source: Epoch AI — AI Benchmarking Hub
Code Arena (WebDev)LeaderboardCoding

1,250

4% expected win rate against the board leader (1,797)
8th percentile of 86

board 2026-09-05

Source: Arena (LMArena) — Leaderboard Dataset

70.0%

70.0% of the best (100.0%)
6th percentile of 78 · n = 45

none

Source: Epoch AI — AI Benchmarking Hub
Text ArenaLeaderboardHuman preference

1,395

34% expected win rate against the board leader (1,507)
8th percentile of 92

board 2026-09-02

Source: Arena (LMArena) — Leaderboard Dataset

Top of the leaderboard

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