Laguna S 2.1 vs Solar Pro 3
Laguna S 2.1 costs 3.3x less per output token than Solar Pro 3 ($0.18 vs $0.60 per million). Updated October 22, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- No data
- Output $/M
- $0.18
- Coding
- No data
- Overall
- No data
- Output $/M
- $0.60
Laguna S 2.1 or Solar Pro 3: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Laguna S 2.1 for output tokens 3.3x cheaper ($0.18 vs $0.60 per million) and a larger context window (1.05M against 131K tokens).
No benchmark has tested both yet. Laguna S 2.1 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
Laguna S 2.1
Laguna S 2.1 takes 1.05M tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Laguna S 2.1
Laguna S 2.1 $0.0002, Solar Pro 3 $0.0004 per turn.
List prices
At a glance
- Coding index
- Laguna S 2.1 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
- Laguna S 2.1 $0.18 against Solar Pro 3 $0.60 per million output tokens, 3.3x apart.
- Context window
- Laguna S 2.1 takes 1.05M 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 | Laguna S 2.1 | 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 | Laguna S 2.1 | 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 | Laguna S 2.1 | 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 | Laguna S 2.1 | 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 | Laguna S 2.1 | 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
Laguna S 2.1 costs less
Repository review
50K input + 3K output tokens
Laguna S 2.1 costs less
Agent loop
200K input + 10K output tokens
Laguna S 2.1 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 | Poolside Laguna S 2.1 | Upstage Solar Pro 3 |
|---|---|---|
| Maker | Poolside | Upstage |
| Weights | Open weights | No public weights listed |
| Released | July 21, 2026 | January 27, 2026 |
| Context window | 1.05M | 131K |
| Input $/Mtok | $0.09 | $0.15 |
| Output $/Mtok | $0.18 | $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 Laguna S 2.1 better than Solar Pro 3 for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Laguna S 2.1 for output tokens 3.3x cheaper ($0.18 vs $0.60 per million) and a larger context window (1.05M against 131K tokens).
Which is cheaper, Laguna S 2.1 or Solar Pro 3?
Laguna S 2.1 costs $0.09 per million input tokens and $0.18 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, Laguna S 2.1 or Solar Pro 3?
Laguna S 2.1, with 1.05M tokens against 131K.
Has any benchmark tested both Laguna S 2.1 and Solar Pro 3?
No benchmark has tested both yet. Laguna S 2.1 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.