Qwen3.5-35B-A3B qwen3.5-35b-a3b

qwen · qwen reasoning efficient

#41 overall #23 agentic

params
36B (A3B)
arch
moe
context
256k
license
apache-2.0 open weights
released
Feb 2026
reasoning
yes
downloads/30d
1.5M

# architecture

attn shared · reasoning GQA 16q/2kv router top-8 of 256 expert ×256 expert out ×40 layers ctx 262,144 36B pool · A3B/token
layers
40
d_model
2048
heads
16q / 2kv
head dim
256
experts
top-8 of 256
vocab
248320
family
qwen3_5_moe_text

signal path of one layer, generated from the registry's structured fields — dimension lines quote the model's real numbers; an MoE trace forks at the router, a dense trace runs straight through. Geometry fields come from the repo's config.json.

# why ranked

Overall: #41 — score 61.5 ● high — all signals present

signalweightinput (0–100)
aa_intelligence 0.70 62.6
bench_composite 0.30 59.0

benchmark panel evidence:

complete panelscore (0–100)
aa-coding-v152.8
browsecomp-v165.2

Coding: provisional — score 42.6 ● low — a single signal; treat with caution

provisional: too few independent signals for a numbered position — the score is shown, but this model sorts after every ranked model.

signalweightinput (0–100)
aa_coding 0.30 42.6
aider_polyglot 0.30 —
swe_bench_verified 0.40 —

missing signals are dropped and the remaining weights renormalized — never imputed.

Agentic: #23 — score — ● low — a single signal; treat with caution

signalweightinput (0–100)
swe_bench_verified 0.60 —
swe_rebench 0.40 0.0

missing signals are dropped and the remaining weights renormalized — never imputed.

full methodology

# trend

OGM score · last 105 days
OGM score over 105 days
overall rank (up is better)
Overall rank over 105 days

methodology changed during this history window; score movement across that boundary is not model movement. See methodology v6.

# benchmarks

benchmarkscoresourcedate
AA Coding Index 37.0 Artificial Analysis —
AA Intelligence Index 19.3 Artificial Analysis —
Aa-lcr 0.6 / 1 LLM Stats —
Ai2d 0.9 / 1 LLM Stats —
Androidworld-sr 0.7 / 1 LLM Stats —
Babyvision 0.4 / 1 LLM Stats —
Bfcl-v4 0.7 / 1 LLM Stats —
Browsecomp 0.6 / 1 LLM Stats —
Browsecomp-zh 0.7 / 1 LLM Stats —
C-eval 0.9 / 1 LLM Stats —
Cc-ocr 0.8 / 1 LLM Stats —
Charxiv-r 0.8 / 1 LLM Stats —
Codeforces 0.8 / 3000 LLM Stats —
Countbench 1.0 LLM Stats —
Vlmsareblind 1.0 / 1 LLM Stats —
SWE-rebench (resolved) 17.1 SWE-rebench —
SWE-rebench (pass@5) 36.9 SWE-rebench —

# where to run

providerquantctx$/M in$/M out$/M cacheprice srctpsuptime✓
Darkbloomfp4 256k $0.07$0.75$0.03 via openrouter — 100.0%
DeepInfrafp8 256k $0.14$1.00— deepinfra — 100.0% ✓
Parasailfp8 256k $0.15$1.00$0.05 via openrouter — 100.0%
Veniceunknown 250k $0.15$1.00— venice — 100.0% ✓
Alibabaunknown 256k $0.16$1.30— via openrouter — 99.4%
Wandb 262k $0.25$1.25— via litellm — —
AtlasCloudfp8 256k $0.23$1.80— atlascloud — 100.0% ✓
SiliconFlowfp8 256k $0.24$1.80$0.15 openrouter — 100.0% ✓
Novita 256k $0.25$2.00— novita 72 — ✓

sorted by blended price ((3·input + output) / 4 per 1M) · ✓ = the provider's own catalog confirms the offer · "via …" prices are what the aggregator routing the offer charges, not the provider's own list price

source aliases
llmstats
qwen3.5-35b-a3b
openrouter
qwen/qwen3.5-35b-a3b