Schematron V2 Small vs Qwen3.5-27B
Schematron V2 Small costs 6.8x less per output token than Qwen3.5-27B ($0.23 vs $1.56 per million). Updated October 22, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- No data
- Output $/M
- $0.23
- Coding
- No data
- Overall
- No data
- Output $/M
- $1.56
Schematron V2 Small or Qwen3.5-27B: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Schematron V2 Small for output tokens 6.8x cheaper ($0.23 vs $1.56 per million).
No benchmark has tested both yet. Schematron V2 Small has none yet; Qwen3.5-27B on LMArena WebDev, Terminal-Bench Hard (Artificial Analysis run) and WeirdML. 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 Qwen3.5-27B has a AA Intelligence Index result, 22.9.
Directional only
Long documents
Listed context window
Qwen3.5-27B
Qwen3.5-27B takes 262K tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Schematron V2 Small
Schematron V2 Small $0.0002, Qwen3.5-27B $0.0010 per turn.
List prices
At a glance
- Coding index
- Schematron V2 Small not benchmarked, Qwen3.5-27B 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
- Schematron V2 Small $0.23 against Qwen3.5-27B $1.56 per million output tokens, 6.8x apart.
- Context window
- Schematron V2 Small takes 128K tokens, Qwen3.5-27B 262K.
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 Index8 boards measured
| Benchmark | Schematron V2 Small | Qwen3.5-27B | Leader |
|---|---|---|---|
| LMArena WebDev | Not measured | 1358 | Only Qwen3.5-27B measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 32.6% | Only Qwen3.5-27B measured |
| WeirdML | Not measured | 39.5% | Only Qwen3.5-27B measured |
| ALE-Bench | Not measured | 349.4 | Only Qwen3.5-27B measured |
| LMArena Text: coding | Not measured | 1427 | Only Qwen3.5-27B measured |
| LMArena Text: software and IT | Not measured | 1431 | Only Qwen3.5-27B measured |
| LMArena WebDev: React | Not measured | 1346 | Only Qwen3.5-27B measured |
| LMArena WebDev: HTML | Not measured | 1386 | Only Qwen3.5-27B measured |
| Neither model has a result on the other 31 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | Schematron V2 Small | Qwen3.5-27B | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 22.9 | Only Qwen3.5-27B measured |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | Schematron V2 Small | Qwen3.5-27B | Leader |
|---|---|---|---|
| τ²-Bench Telecom | Not measured | 93.9% | Only Qwen3.5-27B measured |
| Vending-Bench 2 | Not measured | $202 | Only Qwen3.5-27B measured |
| Neither model has a result on the other 39 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index7 boards measured
| Benchmark | Schematron V2 Small | Qwen3.5-27B | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | Not measured | 85.8% | Only Qwen3.5-27B measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 23.9% | Only Qwen3.5-27B measured |
| LMArena Text: hard prompts | Not measured | 1415 | Only Qwen3.5-27B measured |
| LMArena Text: expert | Not measured | 1427 | Only Qwen3.5-27B measured |
| LMArena Text: hard prompts in English | Not measured | 1429 | Only Qwen3.5-27B measured |
| LMArena Vision: diagrams | Not measured | 1249 | Only Qwen3.5-27B measured |
| LMArena Vision: homework | Not measured | 1256 | Only Qwen3.5-27B measured |
| Neither model has a result on the other 15 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | Schematron V2 Small | Qwen3.5-27B | Leader |
|---|---|---|---|
| LMArena Text: math | Not measured | 1429 | Only Qwen3.5-27B measured |
| LMArena Text: mathematical work | Not measured | 1429 | Only Qwen3.5-27B measured |
| Neither model has a result on the other 11 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index4 boards measured
| Benchmark | Schematron V2 Small | Qwen3.5-27B | Leader |
|---|---|---|---|
| LMArena Text: science | Not measured | 1437 | Only Qwen3.5-27B measured |
| LMArena Text: medicine and healthcare | Not measured | 1425 | Only Qwen3.5-27B measured |
| LMArena Text: legal and government | Not measured | 1405 | Only Qwen3.5-27B measured |
| LMArena Text: business and finance | Not measured | 1399 | Only Qwen3.5-27B measured |
| Neither model has a result on the other 14 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index29 boards measured
| Benchmark | Schematron V2 Small | Qwen3.5-27B | Leader |
|---|---|---|---|
| IFBench | Not measured | 75.6% | Only Qwen3.5-27B measured |
| Long context reasoning (AA-LCR) | Not measured | 77.7% | Only Qwen3.5-27B measured |
| DTBench | Not measured | 82.4% | Only Qwen3.5-27B measured |
| LMCA | Not measured | 34.0% | Only Qwen3.5-27B measured |
| LMArena Text | Not measured | 1409 | Only Qwen3.5-27B measured |
| LMArena Text: instruction following | Not measured | 1393 | Only Qwen3.5-27B measured |
| LMArena Text: creative writing | Not measured | 1362 | Only Qwen3.5-27B measured |
| LMArena Vision | Not measured | 1241 | Only Qwen3.5-27B measured |
| LMArena Text: English | Not measured | 1425 | Only Qwen3.5-27B measured |
| LMArena Text: non-English | Not measured | 1390 | Only Qwen3.5-27B measured |
| LMArena Text: Chinese | Not measured | 1478 | Only Qwen3.5-27B measured |
| LMArena Text: German | Not measured | 1392 | Only Qwen3.5-27B measured |
| LMArena Text: Japanese | Not measured | 1346 | Only Qwen3.5-27B measured |
| LMArena Text: Korean | Not measured | 1359 | Only Qwen3.5-27B measured |
| LMArena Text: French | Not measured | 1410 | Only Qwen3.5-27B measured |
| LMArena Text: Spanish | Not measured | 1407 | Only Qwen3.5-27B measured |
| LMArena Text: Russian | Not measured | 1390 | Only Qwen3.5-27B measured |
| LMArena Text: Polish | Not measured | 1375 | Only Qwen3.5-27B measured |
| LMArena Text: multi-turn | Not measured | 1410 | Only Qwen3.5-27B measured |
| LMArena Text: longer queries | Not measured | 1413 | Only Qwen3.5-27B measured |
| LMArena Text: writing and language | Not measured | 1380 | Only Qwen3.5-27B measured |
| LMArena Text: entertainment and media | Not measured | 1363 | Only Qwen3.5-27B measured |
| LMArena Vision: English | Not measured | 1246 | Only Qwen3.5-27B measured |
| LMArena Vision: Chinese | Not measured | 1301 | Only Qwen3.5-27B measured |
| LMArena Vision: reading text | Not measured | 1246 | Only Qwen3.5-27B measured |
| LMArena Vision: humor | Not measured | 1227 | Only Qwen3.5-27B measured |
| LMArena Vision: captioning | Not measured | 1170 | Only Qwen3.5-27B measured |
| LMArena Vision: recognizing things | Not measured | 1210 | Only Qwen3.5-27B measured |
| LMArena Vision: creative writing | Not measured | 1224 | Only Qwen3.5-27B measured |
| Neither model has a result on the other 17 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
Schematron V2 Small costs less
Repository review
50K input + 3K output tokens
Schematron V2 Small costs less
Agent loop
200K input + 10K output tokens
Schematron V2 Small 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 | Inference.net Schematron V2 Small | Qwen3.5-27B |
|---|---|---|
| Maker | Inference.net | Qwen |
| Weights | Open weights | Open weights |
| Released | September 12, 2026 | February 25, 2026 |
| Context window | 128K | 262K |
| Input $/Mtok | $0.05 | $0.195 |
| Output $/Mtok | $0.23 | $1.56 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 1 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Schematron V2 Small better than Qwen3.5-27B for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Schematron V2 Small for output tokens 6.8x cheaper ($0.23 vs $1.56 per million).
Which is cheaper, Schematron V2 Small or Qwen3.5-27B?
Schematron V2 Small costs $0.05 per million input tokens and $0.23 per million output tokens; Qwen3.5-27B costs $0.195 and $1.56. Cost per solved task is known for neither of them.
Which has the bigger context window, Schematron V2 Small or Qwen3.5-27B?
Qwen3.5-27B, with 262K tokens against 128K.
Has any benchmark tested both Schematron V2 Small and Qwen3.5-27B?
No benchmark has tested both yet. Schematron V2 Small has none yet; Qwen3.5-27B on LMArena WebDev, Terminal-Bench Hard (Artificial Analysis run) and WeirdML. Compare them on price and context instead. Data as of October 22, 2026.