Qwen3.6 35B A3B vs Relace Apply 3
Qwen3.6 35B A3B costs 1.3x less per output token than Relace Apply 3 ($1.00 vs $1.25 per million). Updated October 22, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- 45.0
- Output $/M
- $1.00
- Coding
- No data
- Overall
- No data
- Output $/M
- $1.25
Qwen3.6 35B A3B or Relace Apply 3: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Qwen3.6 35B A3B for output tokens 1.3x cheaper ($1.00 vs $1.25 per million) and a larger context window (262K against 256K tokens).
No benchmark has tested both yet. Qwen3.6 35B A3B 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.
Coding
Vibe Coding Index, six public coding benchmarks
No call
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
No call
Only Qwen3.6 35B A3B has a AA Intelligence Index result, 18.2.
Directional only
Agentic work
AA Agentic Index
No call
Only Qwen3.6 35B A3B has a AA Agentic Index result, 13.1.
Directional only
Long documents
Listed context window
Qwen3.6 35B A3B
Qwen3.6 35B A3B takes 262K tokens against 256K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3.6 35B A3B
Qwen3.6 35B A3B $0.0006, Relace Apply 3 $0.0015 per turn.
List prices
At a glance
- Coding index
- Qwen3.6 35B A3B 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
- Qwen3.6 35B A3B $1.00 against Relace Apply 3 $1.25 per million output tokens, 1.3x apart.
- Context window
- Qwen3.6 35B A3B 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 Index5 boards measured
| Benchmark | Qwen3.6 35B A3B | Relace Apply 3 | Leader |
|---|---|---|---|
| AA Coding Index | 41.9 | Not measured | Only Qwen3.6 35B A3B measured |
| SciCode | 36.6% | Not measured | Only Qwen3.6 35B A3B measured |
| Terminal-Bench Hard (Artificial Analysis run) | 34.8% | Not measured | Only Qwen3.6 35B A3B measured |
| Terminal-Bench | 24.6% | Not measured | Only Qwen3.6 35B A3B measured |
| WeirdML | 34.5% | Not measured | Only Qwen3.6 35B A3B measured |
| Neither model has a result on the other 34 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | Qwen3.6 35B A3B | Relace Apply 3 | Leader |
|---|---|---|---|
| AA Intelligence Index | 18.2 | Not measured | Only Qwen3.6 35B A3B measured |
| Epoch Capabilities Index | 143.7 | Not measured | Only Qwen3.6 35B A3B measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | Qwen3.6 35B A3B | Relace Apply 3 | Leader |
|---|---|---|---|
| AA Agentic Index | 13.1 | Not measured | Only Qwen3.6 35B A3B measured |
| τ²-Bench Telecom | 95.3% | Not measured | Only Qwen3.6 35B A3B measured |
| Neither model has a result on the other 39 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index4 boards measured
| Benchmark | Qwen3.6 35B A3B | Relace Apply 3 | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 84.1% | Not measured | Only Qwen3.6 35B A3B measured |
| Humanity's Last Exam (Artificial Analysis run) | 22.2% | Not measured | Only Qwen3.6 35B A3B measured |
| GPQA Diamond (Epoch AI run) | 84.8% | Not measured | Only Qwen3.6 35B A3B measured |
| Mystery game puzzles | 22.0% | Not measured | Only Qwen3.6 35B A3B measured |
| Neither model has a result on the other 18 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | Qwen3.6 35B A3B | Relace Apply 3 | Leader |
|---|---|---|---|
| OTIS Mock AIME | 86.7% | Not measured | Only Qwen3.6 35B A3B measured |
| FrontierMath, tiers 1 to 3 | 20.4% | Not measured | Only Qwen3.6 35B A3B measured |
| Neither model has a result on the other 11 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index5 boards measured
| Benchmark | Qwen3.6 35B A3B | Relace Apply 3 | Leader |
|---|---|---|---|
| IFBench | 64.4% | Not measured | Only Qwen3.6 35B A3B measured |
| Long context reasoning (AA-LCR) | 71.7% | Not measured | Only Qwen3.6 35B A3B measured |
| DTBench | 73.9% | Not measured | Only Qwen3.6 35B A3B measured |
| LMCA | 29.7% | Not measured | Only Qwen3.6 35B A3B measured |
| Surface Evolver Bench | 44.4% | Not measured | Only Qwen3.6 35B A3B measured |
| Neither model has a result on the other 41 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
Qwen3.6 35B A3B costs less
Repository review
50K input + 3K output tokens
Qwen3.6 35B A3B costs less
Agent loop
200K input + 10K output tokens
Qwen3.6 35B A3B 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.
| Specification | Qwen3.6 35B A3B | Relace Apply 3 |
|---|---|---|
| Maker | Qwen | Relace |
| Weights | Open weights | No public weights listed |
| Released | April 27, 2026 | September 26, 2025 |
| Context window | 262K | 256K |
| Input $/Mtok | $0.10 | $0.85 |
| Output $/Mtok | $1.00 | $1.25 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Qwen3.6 35B A3B better than Relace Apply 3 for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Qwen3.6 35B A3B for output tokens 1.3x cheaper ($1.00 vs $1.25 per million) and a larger context window (262K against 256K tokens).
Which is cheaper, Qwen3.6 35B A3B or Relace Apply 3?
Qwen3.6 35B A3B costs $0.10 per million input tokens and $1.00 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, Qwen3.6 35B A3B or Relace Apply 3?
Qwen3.6 35B A3B, with 262K tokens against 256K.
Has any benchmark tested both Qwen3.6 35B A3B and Relace Apply 3?
No benchmark has tested both yet. Qwen3.6 35B A3B 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.