Coding work
Code generation, repair, and software-engineering tasks
Not enough matched evidence
Solar Open 2 is not ranked on the public lane for coding, so no winner is named for coding.
Confidence: limited
GPT-4.1 mini vs Solar Open 2
Updated October 25, 2026. We do not rank this pair: at least one has no public score. Public scores include evidence status and uncertainty.
Share or export
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.
- Shared results
- 1
- GPT-4.1 mini only
- 4
- Solar Open 2 only
- 10
- Like-for-like categories
- 0 / 8
Estimated: GPT-4.1 mini. Conditional ranges do not establish rank confidence.How the comparison works
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.
No workload recommendation clears the current evidence threshold.
Use the matched evidence, workload costs, and sourced specifications below instead of treating a point score as a universal answer.
Show secondary and unsupported calls
Agentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
GPT-4.1 mini and Solar Open 2 are not ranked on the public lane for agentic, so no winner is named for agentic.
Confidence: limitedLong documents
Prompts that approach the documented context limit
No clear pick
The documented context windows are equal.
Confidence: documentedChat turn cost
1K fresh input + 500 output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
Confidence: listed-ratesCache-heavy agent loop cost
200K cached + 20K fresh input + 10K output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
Confidence: rate-fallbackRepository review cost
50K fresh input + 3K output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
Confidence: listed-rates
Which one for a specific job
Choose a job from the LLM Selector's task catalog to see the category row it rests on, under the same basis rules as the table below. A directional row stays directional; choosing a job never creates a winner.
The same task catalog as the LLM Selector. Each job names the evidence surface it rests on; nothing here adds a new score.
16.3GPT-4.1 mini—Solar Open 2
Not comparable · BenchAlign v5.8
The coding row is not comparable on the public lane: at least one model is not measured or not ranked there.
Coding scores combine specific tasks and setups. Match the editor, harness, and effort to your workflow.
Same basis rules as the category table below
What is actually comparable
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
4 GPT-4.1 mini only
1 Shared
10 Solar Open 2 only
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.
SWE-bench VerifiedCoding
Normalized gap 46.8GPT-4.1 mini:23.6%Solar Open 2:70.4%
Bars run 0–100 on each benchmark’s normalized display scale
Category results, on a stated basis
Each row shows the public-lane category score for both models: the BenchAlign v5.8 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- GPT-4.1 mini
- Not ranked
- Solar Open 2
- Not ranked
- Basis
- BenchAlign v5.8 lane · 0 vs 3 public rows
- Reading
- Not comparable
Coding
Not comparable- GPT-4.1 mini
- 16.3
- Estimated · #132/153
- Solar Open 2
- Not ranked
- Basis
- BenchAlign v5.8 lane · 1 vs 2 public rows
- Reading
- Not comparable
Reasoning
Not comparable- GPT-4.1 mini
- 55.2
- Unranked · 2 rankable rows
- Solar Open 2
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Multimodal
Not comparable- GPT-4.1 mini
- 51.9
- Unranked · 1 rankable row
- Solar Open 2
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Knowledge
Not comparable- GPT-4.1 mini
- 30.7
- Supported · #153/187
- Solar Open 2
- Not ranked
- Basis
- BenchAlign v5.8 lane · 2 vs 3 public rows
- Reading
- Not comparable
Multilingual
Not comparable- GPT-4.1 mini
- Not ranked
- Solar Open 2
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Instruction following
Not comparable- GPT-4.1 mini
- 44.2
- #111/153
- Solar Open 2
- Not ranked
- Basis
- Provisional lane · 0 vs 1 weighted rows
- Reading
- Not comparable
Math
Not comparable- GPT-4.1 mini
- 27.0
- Unranked · 1 rankable row
- Solar Open 2
- Not ranked
- Basis
- Provisional lane · 1 vs 2 weighted rows
- Reading
- Not comparable
| Category | GPT-4.1 mini | Solar Open 2 | Basis | Reading |
|---|---|---|---|---|
| Agentic | Not ranked | Not ranked | Not comparableBenchAlign v5.8 lane · 0 vs 3 public rows | Not comparable |
| Coding | 16.3Estimated · #132/153 | Not ranked | Not comparableBenchAlign v5.8 lane · 1 vs 2 public rows | Not comparable |
| Reasoning | 55.2Unranked · 2 rankable rows | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Multimodal | 51.9Unranked · 1 rankable row | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Knowledge | 30.7Supported · #153/187 | Not ranked | Not comparableBenchAlign v5.8 lane · 2 vs 3 public rows | Not comparable |
| Multilingual | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Instruction following | 44.2#111/153 | Not ranked | Not comparableProvisional lane · 0 vs 1 weighted rows | Not comparable |
| Math | 27.0Unranked · 1 rankable row | Not ranked | Not comparableProvisional lane · 1 vs 2 weighted rows | Not comparable |
Ranks count the models scored in each category’s lane, so the agentic, coding, and knowledge denominators (BenchAlign v5.8) differ from the provisional-lane categories. Unranked scores sit on the provisional lane’s scale but never name a winner. Like-for-like rows within 0.5 points read as a practical tie.
Supported evidence per lane · bars run 0–100Methodology
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
- GPT-4.1 mini
- $0.0012
- Fits in one request
- Solar Open 2
- Self-hosted; infrastructure cost varies
- Fits in one request
Solar Open 2 has no comparable published API token rate.
Repository review
50K fresh input + 3K output tokens
- GPT-4.1 mini
- $0.0248
- Fits in one request
- Solar Open 2
- Self-hosted; infrastructure cost varies
- Fits in one request
Solar Open 2 has no comparable published API token rate.
Cache-heavy agent loop
200K cached + 20K fresh input + 10K output tokens
- GPT-4.1 mini
- $0.104
- Fits in one request
- Cached input priced at the published list-input rate
- Solar Open 2
- Self-hosted; infrastructure cost varies
- Fits in one request
- Cached-input rate unavailable
GPT-4.1 mini has no published cached-input rate, so cached tokens use its listed input rate. Solar Open 2 has no comparable published API token rate.
Cached input falls back to the list input rate only where a cached rate is unpublished
Specification differences
Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.
SpecificationGPT-4.1 miniSolar Open 2
Context window
Maximum documented context; output-token limits may be lower.
GPT-4.1 mini
1M
Solar Open 2
API model ID
GPT-4.1 mini
Not sourced
Solar Open 2
upstage/Solar-Open2-250B
Upstage Solar Open 2 model cardCached-input rate
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
GPT-4.1 mini
Not published
Solar Open 2
No comparable hosted API rate
Upstage Solar Open 2 model cardDocumented inputs
GPT-4.1 mini
Not sourced
Solar Open 2
Not sourced
Documented outputs
GPT-4.1 mini
Not sourced
Solar Open 2
Not sourced
Provider availability
GPT-4.1 mini
Not sourced
Solar Open 2
Not sourced
Reasoning profile
GPT-4.1 mini
Non-Reasoning
Solar Open 2
Reasoning
Weight access
GPT-4.1 mini
Proprietary
Solar Open 2
Open Weight
License
GPT-4.1 mini
Proprietary
Solar Open 2
Open Weight
Release date
GPT-4.1 mini
2025-04-14
Solar Open 2
2026-07-22
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
- A complete comparable API-rate estimate is not available for both models.
- Context tradeoff
- Both models list 1M.
Run the same representative tasks against both endpoints before changing production traffic.
Questions
Which is better, GPT-4.1 mini or Solar Open 2?
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, GPT-4.1 mini or Solar Open 2?
Solar Open 2 is not ranked on the public lane for coding, so no winner is named for coding.
Which is better for agentic tasks, GPT-4.1 mini or Solar Open 2?
GPT-4.1 mini and Solar Open 2 are not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.
Which costs less, GPT-4.1 mini or Solar Open 2?
Both models do not have comparable published API token rates, so this page does not name a universal price winner.
Which has the larger context window, GPT-4.1 mini or Solar Open 2?
Both models list the same context window, 1M.
Self-host vs API cost
Estimates at 50,000 req/day · 1000 tokens/req average.
GPT-4.1 mini
API / mo$1,500
Self-host / moNot listed
Break-even—
Proprietary model — self-hosting not applicable.
Solar Open 2
API / mo$0
Self-host / mo$13,981
Break-even—
Benchmark evidence
The full public result ledger is available for audit without forcing a wide desktop table onto a phone.
Browse raw public benchmark evidence15 rows
Agentic
Coding
Knowledge
MMLU
GPT-4.1 mini87.5%SourceSolar Open 2—Not directly comparable
GPQA
GPT-4.1 mini64.2%SourceSolar Open 2—Not directly comparable
MMLU-Pro
GPT-4.1 mini—Solar Open 286.2%SourceNot directly comparable
GPQA-D
GPT-4.1 mini—Solar Open 286.3%SourceNot directly comparable
HLE w/o tools
GPT-4.1 mini—Solar Open 228.8%SourceNot directly comparable
Instruction following
Math
15 public results · 1 shared
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Last updated October 25, 2026