Instruction following
Like-for-like- Mercury 2.5
- 80.1
- #54/123
- Solar Pro 3
- 87.1
- #35/123
- Basis
- Provisional lane · 1 vs 1 weighted rows
- Reading
- Solar Pro 3 leads
Mercury 2.5 vs Solar Pro 3
Updated September 10, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.
Decision reading
At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner.
1 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.
Share or export
Which one for your work
Recommendations appear only when a shared evidence basis or an explicit operating constraint supports the call. Secondary and unsupported use cases stay disclosed below the initial list.
Long documents
Prompts that approach the documented context limit
Mercury 2.5
Mercury 2.5 has the larger documented context window.
Confidence: documented
Chat turn cost
1K fresh input + 500 output tokens
Mercury 2.5
Mercury 2.5 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
Show secondary and unsupported calls
Repository review cost
50K fresh input + 3K output tokens
Mercury 2.5
Mercury 2.5 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
Coding work
Code generation, repair, and software-engineering tasks
Not enough matched evidence
Solar Pro 3 is not ranked on the public lane for coding, so no winner is named for coding.
Confidence: limited
Agentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
Solar Pro 3 is not ranked on the public lane for agentic, so no winner is named for agentic.
Confidence: limited
Cache-heavy agent loop cost
200K cached + 20K fresh input + 10K output tokens
Not enough matched evidence
The page does not recommend a cost winner because at least one model cannot fit the stated workload in one request. Solar Pro 3 does not fit this workload in one request. Solar Pro 3 has no published cached-input rate, so cached tokens use its listed input rate.
Confidence: rate-fallback
What is actually comparable
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
4 Mercury 2.5 only
1 Shared
- Shared results
- 1
- Mercury 2.5 only
- 4
- Solar Pro 3 only
- 0
- Like-for-like categories
- 1 / 8
Category results, on a stated basis
Each row shows the public-lane category score for both models: the BenchAlign lane for agentic, coding, and knowledge, and the weighted public rows elsewhere, with the same rank each model page reports. A row is like-for-like only when both scores rest on Supported evidence or the same weighted set. Directional and not-comparable rows remain visible, but they never receive a winner.
Agentic
Not comparable- Mercury 2.5
- 44.0
- Estimated · #92/152
- Solar Pro 3
- Not ranked
- Basis
- BenchAlign lane · 2 vs 0 public rows
- Reading
- Not comparable
Coding
Not comparable- Mercury 2.5
- 47.1
- Estimated · #73/151
- Solar Pro 3
- Not ranked
- Basis
- BenchAlign lane · 1 vs 0 public rows
- Reading
- Not comparable
Reasoning
Not comparable- Mercury 2.5
- 67.7
- Unranked · 1 rankable row
- Solar Pro 3
- 43.2
- Unranked · 2 rankable rows
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Knowledge
Not comparable- Mercury 2.5
- 47.6
- Estimated · #94/183
- Solar Pro 3
- Not ranked
- Basis
- BenchAlign lane · 1 vs 0 public rows
- Reading
- Not comparable
Math
Not comparable- Mercury 2.5
- Not ranked
- Solar Pro 3
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Multilingual
Not comparable- Mercury 2.5
- Not ranked
- Solar Pro 3
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Multimodal
Not comparable- Mercury 2.5
- Not ranked
- Solar Pro 3
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
| Category | Mercury 2.5 | Solar Pro 3 | Basis | Reading |
|---|---|---|---|---|
| Instruction following | 80.1#54/123 | 87.1#35/123 | Like-for-likeProvisional lane · 1 vs 1 weighted rows | Solar Pro 3 leads |
| Agentic | 44.0Estimated · #92/152 | Not ranked | Not comparableBenchAlign lane · 2 vs 0 public rows | Not comparable |
| Coding | 47.1Estimated · #73/151 | Not ranked | Not comparableBenchAlign lane · 1 vs 0 public rows | Not comparable |
| Reasoning | 67.7Unranked · 1 rankable row | 43.2Unranked · 2 rankable rows | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Knowledge | 47.6Estimated · #94/183 | Not ranked | Not comparableBenchAlign lane · 1 vs 0 public rows | Not comparable |
| Math | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Multilingual | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Multimodal | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
Ranks count the models scored in each category’s lane, so the agentic, coding, and knowledge denominators (BenchAlign) differ from the provisional-lane categories. Unranked scores sit on the lane’s scale but never name a winner. Like-for-like rows within 0.5 points read as a practical tie.
Shape of the matched evidence
Only shared public evidence is shown. Sparse evidence stays a ruled list rather than being closed into a radar shape.
Too few matched category axes support a radar. The ruled list below shows only shared benchmark results; positions use each benchmark’s normalized display scale when available.
IFBench
Instruction following
What each workload costs
Three fixed token mixes turn per-token rates into comparable decisions. Each scenario states context fit and whether cached input had to fall back to the published list-input rate.
Chat turn
1K fresh input + 500 output tokens
- Mercury 2.5
- $0.00012
- Fits in one request
- Solar Pro 3
- $0.00045
- Fits in one request
Mercury 2.5 has the lower modeled cost
Costs use the listed standard API rates.
Repository review
50K fresh input + 3K output tokens
- Mercury 2.5
- $0.00245
- Fits in one request
- Solar Pro 3
- $0.0093
- Fits in one request
Mercury 2.5 has the lower modeled cost
Costs use the listed standard API rates.
Cache-heavy agent loop
200K cached + 20K fresh input + 10K output tokens
- Mercury 2.5
- $0.0031
- Fits in one request
- Solar Pro 3
- $0.039
- Does not fit in one request
- Cached input priced at the published list-input rate
Solar Pro 3 does not fit this workload in one request. Solar Pro 3 has no published cached-input rate, so cached tokens use its listed input rate.
Specification differences
Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.
SpecificationMercury 2.5Solar Pro 3
Context window
Maximum documented context; output-token limits may be lower.
Mercury 2.5
Solar Pro 3
API model ID
Mercury 2.5
Solar Pro 3
solar-pro3
Upstage API pricingCached-input rate
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
Mercury 2.5
$0.004 per 1M cached input tokens
Inception models and Mercury 2.5 launch pricingSolar Pro 3
Not published
Upstage API pricingDocumented inputs
Mercury 2.5
Not sourced
Solar Pro 3
Not sourced
Documented outputs
Mercury 2.5
Not sourced
Solar Pro 3
Not sourced
Provider availability
Mercury 2.5
Not sourced
Solar Pro 3
Not sourced
Reasoning profile
Mercury 2.5
Reasoning
Solar Pro 3
Reasoning
Weight access
Mercury 2.5
Proprietary
Solar Pro 3
Proprietary
License
Mercury 2.5
Proprietary
Solar Pro 3
Proprietary
Release date
Mercury 2.5
2026-09-08
Solar Pro 3
2026-01-26
If you already use one of these models
- Deployment change
- The models list different providers, so authentication, endpoint behavior, limits, and feature support may change.
- Quality signal
- At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner.
- Workload cost
- Repository review: $0.00245 vs $0.0093. Cache-heavy agent loop: $0.0031 vs $0.039.
- Context tradeoff
- Mercury 2.5 has the larger documented window (260K).
Run the same representative tasks against both endpoints before changing production traffic.
Benchmark evidence
The full public result ledger is available for audit without forcing a wide desktop table onto a phone.
Frequently asked questions
Which is better, Mercury 2.5 or Solar Pro 3?
At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner. The page therefore keeps the decision tied to the specific documented workload.
Which is better for coding, Mercury 2.5 or Solar Pro 3?
Solar Pro 3 is not ranked on the public lane for coding, so no winner is named for coding.
Which is better for agentic tasks, Mercury 2.5 or Solar Pro 3?
Solar Pro 3 is not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.
Which costs less, Mercury 2.5 or Solar Pro 3?
For the stated presets, chat costs $0.00012 on Mercury 2.5 and $0.00045 on Solar Pro 3; repository review costs $0.00245 and $0.0093; the cache-heavy agent loop costs $0.0031 and $0.039. Solar Pro 3 does not fit this workload in one request. Solar Pro 3 has no published cached-input rate, so cached tokens use its listed input rate.
Which has the larger context window, Mercury 2.5 or Solar Pro 3?
Mercury 2.5 has the larger documented context window: 260K, compared with 128K.
Related comparisons
Last updated September 10, 2026
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