Schematron V2 Turbo vs Solar Pro 3
Schematron V2 Turbo costs 4.0x less per output token than Solar Pro 3 ($0.15 vs $0.60 per million). Updated October 22, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- No data
- Output $/M
- $0.15
- Coding
- No data
- Overall
- No data
- Output $/M
- $0.60
Schematron V2 Turbo or Solar Pro 3: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Schematron V2 Turbo for output tokens 4.0x cheaper ($0.15 vs $0.60 per million).
No benchmark has tested both yet. Schematron V2 Turbo has none yet; Solar Pro 3 on AA Coding Index, SciCode and Terminal-Bench Hard (Artificial Analysis run). 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 Solar Pro 3 has a AA Intelligence Index result, 7.8.
Directional only
Agentic work
AA Agentic Index
No call
Only Solar Pro 3 has a AA Agentic Index result, 1.4.
Directional only
Long documents
Listed context window
Solar Pro 3
Solar Pro 3 takes 131K tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Schematron V2 Turbo
Schematron V2 Turbo $0.0001, Solar Pro 3 $0.0004 per turn.
List prices
At a glance
- Coding index
- Schematron V2 Turbo not benchmarked, Solar Pro 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
- Schematron V2 Turbo $0.15 against Solar Pro 3 $0.60 per million output tokens, 4.0x apart.
- Context window
- Schematron V2 Turbo takes 128K tokens, Solar Pro 3 131K.
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 Index3 boards measured
| Benchmark | Schematron V2 Turbo | Solar Pro 3 | Leader |
|---|---|---|---|
| AA Coding Index | Not measured | 16.2 | Only Solar Pro 3 measured |
| SciCode | Not measured | 25.5% | Only Solar Pro 3 measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 7.6% | Only Solar Pro 3 measured |
| Neither model has a result on the other 40 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | Schematron V2 Turbo | Solar Pro 3 | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 7.8 | Only Solar Pro 3 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 Turbo | Solar Pro 3 | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 1.4 | Only Solar Pro 3 measured |
| τ²-Bench Telecom | Not measured | 86.3% | Only Solar Pro 3 measured |
| Neither model has a result on the other 40 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | Schematron V2 Turbo | Solar Pro 3 | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | Not measured | 72.4% | Only Solar Pro 3 measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 10.3% | Only Solar Pro 3 measured |
| Neither model has a result on the other 21 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | Schematron V2 Turbo | Solar Pro 3 | Leader |
|---|---|---|---|
| IFBench | Not measured | 71.2% | Only Solar Pro 3 measured |
| Long context reasoning (AA-LCR) | Not measured | 32.3% | Only Solar Pro 3 measured |
| Neither model has a result on the other 46 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 Turbo costs less
Repository review
50K input + 3K output tokens
Schematron V2 Turbo costs less
Agent loop
200K input + 10K output tokens
Schematron V2 Turbo 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 Turbo | Upstage Solar Pro 3 |
|---|---|---|
| Maker | Inference.net | Upstage |
| Weights | Open weights | No public weights listed |
| Released | September 12, 2026 | January 27, 2026 |
| Context window | 128K | 131K |
| Input $/Mtok | $0.03 | $0.15 |
| Output $/Mtok | $0.15 | $0.60 |
| 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 Schematron V2 Turbo better than Solar Pro 3 for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Schematron V2 Turbo for output tokens 4.0x cheaper ($0.15 vs $0.60 per million).
Which is cheaper, Schematron V2 Turbo or Solar Pro 3?
Schematron V2 Turbo costs $0.03 per million input tokens and $0.15 per million output tokens; Solar Pro 3 costs $0.15 and $0.60. Cost per solved task is known for neither of them.
Which has the bigger context window, Schematron V2 Turbo or Solar Pro 3?
Solar Pro 3, with 131K tokens against 128K.
Has any benchmark tested both Schematron V2 Turbo and Solar Pro 3?
No benchmark has tested both yet. Schematron V2 Turbo has none yet; Solar Pro 3 on AA Coding Index, SciCode and Terminal-Bench Hard (Artificial Analysis run). Compare them on price and context instead. Data as of October 22, 2026.