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Qwen3.5-9B vs Relace Apply 3

Qwen3.5-9B costs 8.3x less per output token than Relace Apply 3 ($0.15 vs $1.25 per million). Updated October 22, 2026; no benchmark has tested both models yet.

Qwen3.5-9BQwen
Coding
No data
Overall
No data
Output $/M
$0.15
Relace Apply 3Relace
Coding
No data
Overall
No data
Output $/M
$1.25
vs $0.15 vs $1.25 per 1M output tokens. Qwen3.5-9B is 8.3x cheaper.

Qwen3.5-9B or Relace Apply 3: which to pick

Neither model has a coding score yet, so the two cannot be ranked on coding.

Pick Qwen3.5-9B for output tokens 8.3x cheaper ($0.15 vs $1.25 per million) and a larger context window (262K against 256K tokens).

No benchmark has tested both yet. Qwen3.5-9B has results on AA Coding Index, SciCode and Terminal-Bench Hard (Artificial Analysis run); Relace Apply 3 has none yet. Compare them on price and context instead.

Which one for your work

Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.

At a glance

Coding index
Qwen3.5-9B not benchmarked, Relace Apply 3 not benchmarked.
Widest category
None yet: no category has been tested on both models.
Widest single gap
None yet: no benchmark has tested both models.
Output price
Qwen3.5-9B $0.15 against Relace Apply 3 $1.25 per million output tokens, 8.3x apart.
Context window
Qwen3.5-9B takes 262K tokens, Relace Apply 3 256K.

Benchmark by benchmark

Every board either model has a result on, a category to a fold; bars are each result on a 0 to 100 scale. Only one model is measured on each, so no row names a leader.

CodingDirectional onlySix of these boards feed the Vibe Coding Index4 boards measured
Coding benchmarks for Qwen3.5-9B and Relace Apply 3
BenchmarkQwen3.5-9BRelace Apply 3Leader
AA Coding Index23.5Not measuredOnly Qwen3.5-9B measured
SciCode29.5%Not measuredOnly Qwen3.5-9B measured
Terminal-Bench Hard (Artificial Analysis run)24.2%Not measuredOnly Qwen3.5-9B measured
Terminal-Bench9.2%Not measuredOnly Qwen3.5-9B measured
Neither model has a result on the other 35 boards here
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
Intelligence benchmarks for Qwen3.5-9B and Relace Apply 3
BenchmarkQwen3.5-9BRelace Apply 3Leader
AA Intelligence Index13.3Not measuredOnly Qwen3.5-9B measured
Epoch Capabilities Index139.3Not measuredOnly Qwen3.5-9B measured
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
Agentic work benchmarks for Qwen3.5-9B and Relace Apply 3
BenchmarkQwen3.5-9BRelace Apply 3Leader
τ²-Bench Telecom86.8%Not measuredOnly Qwen3.5-9B measured
Neither model has a result on the other 40 boards here
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index3 boards measured
Reasoning benchmarks for Qwen3.5-9B and Relace Apply 3
BenchmarkQwen3.5-9BRelace Apply 3Leader
GPQA Diamond (Artificial Analysis run)80.6%Not measuredOnly Qwen3.5-9B measured
Humanity's Last Exam (Artificial Analysis run)14.9%Not measuredOnly Qwen3.5-9B measured
GPQA Diamond (Epoch AI run)79.0%Not measuredOnly Qwen3.5-9B measured
Neither model has a result on the other 19 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
Math benchmarks for Qwen3.5-9B and Relace Apply 3
BenchmarkQwen3.5-9BRelace Apply 3Leader
OTIS Mock AIME61.7%Not measuredOnly Qwen3.5-9B measured
Neither model has a result on the other 12 boards here
GeneralDirectional onlyPublic boards, shown as published, kept out of the index4 boards measured
General benchmarks for Qwen3.5-9B and Relace Apply 3
BenchmarkQwen3.5-9BRelace Apply 3Leader
IFBench66.7%Not measuredOnly Qwen3.5-9B measured
Long context reasoning (AA-LCR)70.0%Not measuredOnly Qwen3.5-9B measured
DTBench71.2%Not measuredOnly Qwen3.5-9B measured
LMCA24.5%Not measuredOnly Qwen3.5-9B measured
Neither model has a result on the other 42 boards here

What each workload costs

Three fixed token mixes at each model's listed price, so per-token rates become a bill.

Chat turn

1K input + 500 output tokens

Qwen3.5-9B$0.0002Fits in one request
Relace Apply 3$0.0015Fits in one request

Qwen3.5-9B costs less

Repository review

50K input + 3K output tokens

Qwen3.5-9B$0.0054Fits in one request
Relace Apply 3$0.046Fits in one request

Qwen3.5-9B costs less

Agent loop

200K input + 10K output tokens

Qwen3.5-9B$0.021Fits in one request
Relace Apply 3$0.182Fits in one request

Qwen3.5-9B costs less

Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.

Specification differences

The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.

Specifications of Qwen3.5-9B and Relace Apply 3
SpecificationQwen3.5-9BRelace Apply 3
MakerQwenRelace
WeightsOpen weightsNo public weights listed
ReleasedMarch 10, 2026September 26, 2025
Context window262K256K
Input $/Mtok$0.10$0.85
Output $/Mtok$0.15$1.25
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Qwen3.5-9B better than Relace Apply 3 for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Qwen3.5-9B for output tokens 8.3x cheaper ($0.15 vs $1.25 per million) and a larger context window (262K against 256K tokens).

Which is cheaper, Qwen3.5-9B or Relace Apply 3?

Qwen3.5-9B costs $0.10 per million input tokens and $0.15 per million output tokens; Relace Apply 3 costs $0.85 and $1.25. Cost per solved task is known for neither of them.

Which has the bigger context window, Qwen3.5-9B or Relace Apply 3?

Qwen3.5-9B, with 262K tokens against 256K.

Has any benchmark tested both Qwen3.5-9B and Relace Apply 3?

No benchmark has tested both yet. Qwen3.5-9B has results on AA Coding Index, SciCode and Terminal-Bench Hard (Artificial Analysis run); Relace Apply 3 has none yet. Compare them on price and context instead. Data as of October 22, 2026.

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