Long documents
Prompts that approach the documented context limit
GPT-6.1 Sol
GPT-6.1 Sol has the larger documented context window.
Confidence: documented
GPT-6.1 Sol vs Step 5 Preview
Updated September 29, 2026. Rank says Step 5 Preview is ahead. Price, access, and your workload can each overturn that. Public scores include evidence status and uncertainty.
Both of these models will change. Get the price, version and retirement notices for the pair, each with its source. Follow model changes
Share or export
Decision reading
Step 5 Preview has the higher public score estimate, 68.52 versus 66.86, but the 90% score intervals overlap. Treat that as a lead, not a settled winner. 2 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.
- Shared results
- 2
- GPT-6.1 Sol only
- 7
- Step 5 Preview only
- 20
- Like-for-like categories
- 0 / 8
Estimated: GPT-6.1 Sol and Step 5 PreviewHow 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.
Chat turn cost
1K fresh input + 500 output tokens
Step 5 Preview
Step 5 Preview has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-ratesCache-heavy agent loop cost
200K cached + 20K fresh input + 10K output tokens
Step 5 Preview
Step 5 Preview 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
Step 5 Preview
Step 5 Preview has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-ratesCoding work
Code generation, repair, and software-engineering tasks
Not enough matched evidence
Step 5 Preview is scored on Estimated evidence for coding, so the reading is directional rather than like-for-like.
Confidence: limitedAgentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
GPT-6.1 Sol is not ranked on the public lane for agentic, so no winner is named for agentic.
Confidence: limited
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.
67.0GPT-6.1 Sol61.4Step 5 Preview
Directional only · BenchAlign v5.7
GPT-6.1 Sol scores higher, but at least one score rests on Estimated evidence or a different benchmark set. Directional only, no winner.
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.
7 GPT-6.1 Sol only
2 Shared
20 Step 5 Preview only
2 categories rest on Estimated evidence or different evidence sets. Those rows remain visible for coverage context but do not name a winner.
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.
AutomationBenchAgentic
Normalized gap 7.9GPT-6.1 Sol:36.1%Step 5 Preview:44.0%
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 v5.7 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.
Coding
Directional only- GPT-6.1 Sol
- 67.0
- Supported · #8/143
- Step 5 Preview
- 61.4
- Estimated · #18/143
- Basis
- BenchAlign v5.7 lane · 1 vs 6 public rows
- Reading
- Directional only
Knowledge
Directional only- GPT-6.1 Sol
- 71.3
- Estimated · #10/169
- Step 5 Preview
- 66.8
- Supported · #18/169
- Basis
- BenchAlign v5.7 lane · 5 vs 2 public rows
- Reading
- Directional only
Agentic
Not comparable- GPT-6.1 Sol
- Not ranked
- Step 5 Preview
- 62.1
- Estimated · #14/117
- Basis
- BenchAlign v5.7 lane · 3 vs 11 public rows
- Reading
- Not comparable
Reasoning
Not comparable- GPT-6.1 Sol
- 79.4
- Unranked · 2 rankable rows
- Step 5 Preview
- 79.6
- Unranked · 2 rankable rows
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Multimodal
Not comparable- GPT-6.1 Sol
- 83.9
- Unranked · 1 rankable row
- Step 5 Preview
- 61.2
- #29/50
- Basis
- Provisional lane · 0 vs 2 weighted rows
- Reading
- Not comparable
Multilingual
Not comparable- GPT-6.1 Sol
- Not ranked
- Step 5 Preview
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Instruction following
Not comparable- GPT-6.1 Sol
- Not ranked
- Step 5 Preview
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Math
Not comparable- GPT-6.1 Sol
- Not ranked
- Step 5 Preview
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
| Category | GPT-6.1 Sol | Step 5 Preview | Basis | Reading |
|---|---|---|---|---|
| Coding | 67.0Supported · #8/143 | 61.4Estimated · #18/143 | Directional onlyBenchAlign v5.7 lane · 1 vs 6 public rows | Directional only |
| Knowledge | 71.3Estimated · #10/169 | 66.8Supported · #18/169 | Directional onlyBenchAlign v5.7 lane · 5 vs 2 public rows | Directional only |
| Agentic | Not ranked | 62.1Estimated · #14/117 | Not comparableBenchAlign v5.7 lane · 3 vs 11 public rows | Not comparable |
| Reasoning | 79.4Unranked · 2 rankable rows | 79.6Unranked · 2 rankable rows | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Multimodal | 83.9Unranked · 1 rankable row | 61.2#29/50 | Not comparableProvisional lane · 0 vs 2 weighted rows | Not comparable |
| Multilingual | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Instruction following | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Math | 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 v5.7) 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-6.1 Sol
- $0.007
- Fits in one request
- Step 5 Preview
- $0.00235
- Fits in one request
Step 5 Preview has the lower modeled cost
Costs use the listed standard API rates.
Repository review
50K fresh input + 3K output tokens
- GPT-6.1 Sol
- $0.13
- Fits in one request
- Step 5 Preview
- $0.0581
- Fits in one request
Step 5 Preview has the lower modeled cost
Costs use the listed standard API rates.
Cache-heavy agent loop
200K cached + 20K fresh input + 10K output tokens
- GPT-6.1 Sol
- $0.16
- Fits in one request
- Step 5 Preview
- $0.057
- Fits in one request
Step 5 Preview has the lower modeled cost
Costs use the listed standard API rates.
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-6.1 SolStep 5 Preview
Context window
Maximum documented context; output-token limits may be lower.
GPT-6.1 Sol
Step 5 Preview
API model ID
GPT-6.1 Sol
gpt-6.1-sol
OpenAI GPT-6.1 Sol model documentationStep 5 Preview
step-5-preview
StepFun Step 5 Preview model documentationCached-input rate
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
GPT-6.1 Sol
$0.1 per 1M cached input tokens
OpenAI GPT-6.1 Sol model documentationStep 5 Preview
$0.05 per 1M cached input tokens
StepFun pricing and rate limitsDocumented inputs
GPT-6.1 Sol
text, image
OpenAI GPT-6.1 Sol model documentationStep 5 Preview
text, image, video
StepFun Step 5 Preview model documentationDocumented outputs
GPT-6.1 Sol
Step 5 Preview
Provider availability
GPT-6.1 Sol
Generally Available · OpenAI Responses API, OpenAI Chat Completions API
OpenAI GPT-6.1 Sol model documentationStep 5 Preview
Preview · StepFun Open Platform API
StepFun Step 5 Preview model documentationReasoning profile
GPT-6.1 Sol
Reasoning
Step 5 Preview
Reasoning
Weight access
GPT-6.1 Sol
Proprietary
Step 5 Preview
Pending
License
GPT-6.1 Sol
Proprietary
Step 5 Preview
Pending
Release date
GPT-6.1 Sol
2026-09-29
Step 5 Preview
2026-09-20
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
- Step 5 Preview has the higher public score estimate, 68.52 versus 66.86, but the 90% score intervals overlap.
- Workload cost
- Repository review: $0.13 vs $0.0581. Cache-heavy agent loop: $0.16 vs $0.057.
- Context tradeoff
- GPT-6.1 Sol has the larger documented window (1.05M).
Run the same representative tasks against both endpoints before changing production traffic.
Questions
Which is better, GPT-6.1 Sol or Step 5 Preview?
Step 5 Preview has the higher public score estimate, 68.52 versus 66.86, but the 90% score intervals overlap. The higher estimate is not a decisive winner because the uncertainty ranges overlap.
Which is better for coding, GPT-6.1 Sol or Step 5 Preview?
GPT-6.1 Sol scores higher for coding on the public lane, 67 to 61.4. Step 5 Preview is scored on Estimated evidence for coding, so the reading is directional rather than like-for-like. BenchLM does not name a winner for coding from a directional reading; read the shared benchmark rows directly and test the models on the same task set.
Which is better for agentic tasks, GPT-6.1 Sol or Step 5 Preview?
GPT-6.1 Sol is not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.
Which costs less, GPT-6.1 Sol or Step 5 Preview?
For the stated presets, chat costs $0.007 on GPT-6.1 Sol and $0.00235 on Step 5 Preview; repository review costs $0.13 and $0.0581; the cache-heavy agent loop costs $0.16 and $0.057. Costs use the listed standard API rates.
Which has the larger context window, GPT-6.1 Sol or Step 5 Preview?
GPT-6.1 Sol has the larger documented context window: 1.05M, compared with 1M.
Benchmark evidence
The full public result ledger is available for audit without forcing a wide desktop table onto a phone.
Browse raw public benchmark evidence29 rows
Agentic
AutomationBench
GPT-6.1 Sol36.1%SourceStep 5 Preview44.0%SourceStep 5 Preview leads this result
Terminal-Bench-Science 0.1
GPT-6.1 Sol57.0%SourceStep 5 Preview—Not directly comparable
ExploitGym
GPT-6.1 Sol35.1%SourceStep 5 Preview—Not directly comparable
Terminal-Bench 2.1
GPT-6.1 Sol—Step 5 Preview85.0%SourceNot directly comparable
Terminal-Bench 4.0
GPT-6.1 Sol—Step 5 Preview33.30%SourceNot directly comparable
CyberGym
GPT-6.1 Sol—Step 5 Preview84.7%SourceNot directly comparable
Toolathlon-Verified
GPT-6.1 Sol—Step 5 Preview74.1%SourceNot directly comparable
MCP Atlas
GPT-6.1 Sol—Step 5 Preview85.6%SourceNot directly comparable
JobBench
GPT-6.1 Sol—Step 5 Preview59.0%SourceNot directly comparable
APEX-Agents
GPT-6.1 Sol—Step 5 Preview37.8%SourceNot directly comparable
DRACO
GPT-6.1 Sol—Step 5 Preview83.3%SourceNot directly comparable
BrowseComp
GPT-6.1 Sol—Step 5 Preview88.7%SourceNot directly comparable
Agents' Last Exam
GPT-6.1 Sol—Step 5 Preview29.5%SourceNot directly comparable
Coding
DeepSWE
GPT-6.1 Sol71.9%SourceStep 5 Preview67.7%SourceGPT-6.1 Sol leads this result
Terminal-Bench 2.1
GPT-6.1 Sol—Step 5 Preview85.0%SourceNot directly comparable
SciCode
GPT-6.1 Sol—Step 5 Preview58.9%SourceNot directly comparable
ProgramBench
GPT-6.1 Sol—Step 5 Preview80.5%SourceNot directly comparable
sweMarathon
GPT-6.1 Sol—Step 5 Preview72.7%SourceNot directly comparable
MLS-Bench Lite
GPT-6.1 Sol—Step 5 Preview40.5%SourceNot directly comparable
Reasoning
CritPt
GPT-6.1 Sol—Step 5 Preview20.9%SourceNot directly comparable
Multimodal
Knowledge
HealthBench (raw)
GPT-6.1 Sol56.7%SourceStep 5 Preview—Not directly comparable
HealthBench (length-adjusted)
GPT-6.1 Sol58.5%SourceStep 5 Preview—Not directly comparable
HealthBench Professional
GPT-6.1 Sol64.2%SourceStep 5 Preview—Not directly comparable
HealthBench Professional (raw)
GPT-6.1 Sol67.2%SourceStep 5 Preview—Not directly comparable
HealthBench Hard
GPT-6.1 Sol36.2%SourceStep 5 Preview—Not directly comparable
GPQA-D
GPT-6.1 Sol—Step 5 Preview93.5%SourceNot directly comparable
HLE
GPT-6.1 Sol—Step 5 Preview46.5%SourceNot directly comparable
29 public results · 2 shared
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Last updated September 29, 2026