Long documents
Prompts that approach the documented context limit
GPT-5.5 Pro
GPT-5.5 Pro has the larger documented context window.
Confidence: documented
GPT-5.5 Pro vs Nemotron 3.5 Lightning 30B A3B NVFP4
Updated September 24, 2026. Rank says GPT-5.5 Pro 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
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Decision reading
GPT-5.5 Pro has the higher public score, 72.42 versus 19.1, and the 90% score intervals do not overlap. 2 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.
Model B
NVIDIA
19.1/100
Estimated · Public rank #186
90% interval 9.2–29.0
- Shared results
- 2
- GPT-5.5 Pro only
- 6
- Nemotron 3.5 Lightning 30B A3B NVFP4 only
- 11
- Like-for-like categories
- 0 / 8
Estimated: GPT-5.5 Pro and Nemotron 3.5 Lightning 30B A3B NVFP4How 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.
Show secondary and unsupported calls
Coding work
Code generation, repair, and software-engineering tasks
Not enough matched evidence
GPT-5.5 Pro is not ranked on the public lane for coding, so no winner is named for coding.
Confidence: limitedAgentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
GPT-5.5 Pro is not ranked on the public lane for agentic, so no winner is named for agentic.
Confidence: limitedChat 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.
—GPT-5.5 Pro11.4Nemotron 3.5 Lightning 30B A3B NVFP4
Not comparable · BenchAlign v5.7
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.
6 GPT-5.5 Pro only
2 Shared
11 Nemotron 3.5 Lightning 30B A3B NVFP4 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.
BrowseCompAgentic
Normalized gap 53.3GPT-5.5 Pro:90.1%Nemotron 3.5 Lightning 30B A3B NVFP4:36.8%HLE w/o toolsKnowledge
Normalized gap 32.6GPT-5.5 Pro:43.1%Nemotron 3.5 Lightning 30B A3B NVFP4:10.5%
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.
Agentic
Not comparable- GPT-5.5 Pro
- Not ranked
- Nemotron 3.5 Lightning 30B A3B NVFP4
- 7.3
- Estimated · #104/105
- Basis
- BenchAlign v5.7 lane · 1 vs 4 public rows
- Reading
- Not comparable
Coding
Not comparable- GPT-5.5 Pro
- Not ranked
- Nemotron 3.5 Lightning 30B A3B NVFP4
- 11.4
- Estimated · #135/135
- Basis
- BenchAlign v5.7 lane · 0 vs 4 public rows
- Reading
- Not comparable
Reasoning
Not comparable- GPT-5.5 Pro
- 75.0
- Unranked · 3 rankable rows
- Nemotron 3.5 Lightning 30B A3B NVFP4
- 55.9
- Unranked · 1 rankable row
- Basis
- Provisional lane · 1 vs 0 weighted rows
- Reading
- Not comparable
Multimodal
Not comparable- GPT-5.5 Pro
- Not ranked
- Nemotron 3.5 Lightning 30B A3B NVFP4
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Knowledge
Not comparable- GPT-5.5 Pro
- Not ranked
- Nemotron 3.5 Lightning 30B A3B NVFP4
- 20.7
- Estimated · #154/158
- Basis
- BenchAlign v5.7 lane · 2 vs 4 public rows
- Reading
- Not comparable
Multilingual
Not comparable- GPT-5.5 Pro
- Not ranked
- Nemotron 3.5 Lightning 30B A3B NVFP4
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Instruction following
Not comparable- GPT-5.5 Pro
- Not ranked
- Nemotron 3.5 Lightning 30B A3B NVFP4
- 68.5
- #67/124
- Basis
- Provisional lane · 0 vs 1 weighted rows
- Reading
- Not comparable
Math
Not comparable- GPT-5.5 Pro
- 70.1
- Unranked · 3 rankable rows
- Nemotron 3.5 Lightning 30B A3B NVFP4
- Not ranked
- Basis
- Provisional lane · 2 vs 0 weighted rows
- Reading
- Not comparable
| Category | GPT-5.5 Pro | Nemotron 3.5 Lightning 30B A3B NVFP4 | Basis | Reading |
|---|---|---|---|---|
| Agentic | Not ranked | 7.3Estimated · #104/105 | Not comparableBenchAlign v5.7 lane · 1 vs 4 public rows | Not comparable |
| Coding | Not ranked | 11.4Estimated · #135/135 | Not comparableBenchAlign v5.7 lane · 0 vs 4 public rows | Not comparable |
| Reasoning | 75.0Unranked · 3 rankable rows | 55.9Unranked · 1 rankable row | Not comparableProvisional lane · 1 vs 0 weighted rows | Not comparable |
| Multimodal | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Knowledge | Not ranked | 20.7Estimated · #154/158 | Not comparableBenchAlign v5.7 lane · 2 vs 4 public rows | Not comparable |
| Multilingual | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Instruction following | Not ranked | 68.5#67/124 | Not comparableProvisional lane · 0 vs 1 weighted rows | Not comparable |
| Math | 70.1Unranked · 3 rankable rows | Not ranked | Not comparableProvisional lane · 2 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.
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-5.5 Pro
- $0.12
- Fits in one request
- Nemotron 3.5 Lightning 30B A3B NVFP4
- Self-hosted; infrastructure cost varies
- Fits in one request
Nemotron 3.5 Lightning 30B A3B NVFP4 has no comparable published API token rate.
Repository review
50K fresh input + 3K output tokens
- GPT-5.5 Pro
- $2.04
- Fits in one request
- Nemotron 3.5 Lightning 30B A3B NVFP4
- Self-hosted; infrastructure cost varies
- Fits in one request
Nemotron 3.5 Lightning 30B A3B NVFP4 has no comparable published API token rate.
Cache-heavy agent loop
200K cached + 20K fresh input + 10K output tokens
- GPT-5.5 Pro
- $8.40
- Fits in one request
- Cached input priced at the published list-input rate
- Nemotron 3.5 Lightning 30B A3B NVFP4
- Self-hosted; infrastructure cost varies
- Fits in one request
- Cached-input rate unavailable
GPT-5.5 Pro has no published cached-input rate, so cached tokens use its listed input rate. Nemotron 3.5 Lightning 30B A3B NVFP4 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-5.5 ProNemotron 3.5 Lightning 30B A3B NVFP4
Context window
Maximum documented context; output-token limits may be lower.
GPT-5.5 Pro
Nemotron 3.5 Lightning 30B A3B NVFP4
API model ID
GPT-5.5 Pro
gpt-5.5-pro
OpenAI GPT-5.5 Pro model documentationNemotron 3.5 Lightning 30B A3B NVFP4
Not sourced
Cached-input rate
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
GPT-5.5 Pro
Not published
OpenAI pricingNemotron 3.5 Lightning 30B A3B NVFP4
No comparable hosted API rate
NVIDIA Nemotron 3.5 Lightning model cardDocumented inputs
GPT-5.5 Pro
text, image
OpenAI model catalogNemotron 3.5 Lightning 30B A3B NVFP4
Not sourced
Documented outputs
GPT-5.5 Pro
Nemotron 3.5 Lightning 30B A3B NVFP4
Not sourced
Provider availability
GPT-5.5 Pro
Generally Available · OpenAI Responses API
OpenAI model catalogNemotron 3.5 Lightning 30B A3B NVFP4
Not sourced
Reasoning profile
GPT-5.5 Pro
Reasoning
Nemotron 3.5 Lightning 30B A3B NVFP4
Reasoning
Weight access
GPT-5.5 Pro
Proprietary
Nemotron 3.5 Lightning 30B A3B NVFP4
Open Weight
License
GPT-5.5 Pro
Proprietary
Nemotron 3.5 Lightning 30B A3B NVFP4
Open Weight
Release date
GPT-5.5 Pro
2026-04-23
Nemotron 3.5 Lightning 30B A3B NVFP4
2026-08-11
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
- GPT-5.5 Pro has the higher public score, 72.42 versus 19.1, and the 90% score intervals do not overlap.
- Workload cost
- A complete comparable API-rate estimate is not available for both models.
- Context tradeoff
- GPT-5.5 Pro has the larger documented window (1.05M).
Run the same representative tasks against both endpoints before changing production traffic.
Questions
Which is better, GPT-5.5 Pro or Nemotron 3.5 Lightning 30B A3B NVFP4?
GPT-5.5 Pro has the higher public score, 72.42 versus 19.1, and the 90% score intervals do not overlap. That is the clearest overall quality signal in the current public data.
Which is better for coding, GPT-5.5 Pro or Nemotron 3.5 Lightning 30B A3B NVFP4?
GPT-5.5 Pro is not ranked on the public lane for coding, so no winner is named for coding.
Which is better for agentic tasks, GPT-5.5 Pro or Nemotron 3.5 Lightning 30B A3B NVFP4?
GPT-5.5 Pro is not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.
Which costs less, GPT-5.5 Pro or Nemotron 3.5 Lightning 30B A3B NVFP4?
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-5.5 Pro or Nemotron 3.5 Lightning 30B A3B NVFP4?
GPT-5.5 Pro 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 evidence19 rows
Agentic
BrowseComp
GPT-5.5 Pro90.1%SourceNemotron 3.5 Lightning 30B A3B NVFP436.8%SourceGPT-5.5 Pro leads this result
Terminal-Bench 2.1
GPT-5.5 Pro—Nemotron 3.5 Lightning 30B A3B NVFP423.5%SourceNot directly comparable
PinchBench
GPT-5.5 Pro—Nemotron 3.5 Lightning 30B A3B NVFP483.4%SourceNot directly comparable
τ³-bench results
GPT-5.5 Pro—Nemotron 3.5 Lightning 30B A3B NVFP49.5%SourceNot directly comparable
Coding
SWE-bench Verified
GPT-5.5 Pro—Nemotron 3.5 Lightning 30B A3B NVFP452.8%SourceNot directly comparable
SWE Multilingual
GPT-5.5 Pro—Nemotron 3.5 Lightning 30B A3B NVFP436.5%SourceNot directly comparable
Terminal-Bench 2.1
GPT-5.5 Pro—Nemotron 3.5 Lightning 30B A3B NVFP423.5%SourceNot directly comparable
SciCode
GPT-5.5 Pro—Nemotron 3.5 Lightning 30B A3B NVFP431.4%SourceNot directly comparable
Reasoning
Knowledge
HLE
GPT-5.5 Pro57.2%SourceNemotron 3.5 Lightning 30B A3B NVFP4—Not directly comparable
HLE w/o tools
GPT-5.5 Pro43.1%SourceNemotron 3.5 Lightning 30B A3B NVFP410.5%SourceGPT-5.5 Pro leads this result
GPQA
GPT-5.5 Pro—Nemotron 3.5 Lightning 30B A3B NVFP475.6%SourceNot directly comparable
GPQA-D
GPT-5.5 Pro—Nemotron 3.5 Lightning 30B A3B NVFP475.6%SourceNot directly comparable
MMLU-Pro
GPT-5.5 Pro—Nemotron 3.5 Lightning 30B A3B NVFP481.6%SourceNot directly comparable
Instruction following
IFBench
GPT-5.5 Pro—Nemotron 3.5 Lightning 30B A3B NVFP472.9%SourceNot directly comparable
Math
FrontierMath (legacy)
GPT-5.5 Pro52.4%SourceNemotron 3.5 Lightning 30B A3B NVFP4—Not directly comparable
FrontierMath v2 (Tiers 1-3)
GPT-5.5 Pro51.000%SourceNemotron 3.5 Lightning 30B A3B NVFP4—Not directly comparable
FrontierMath v2 (Tier 4)
GPT-5.5 Pro39.600%SourceNemotron 3.5 Lightning 30B A3B NVFP4—Not directly comparable
19 public results · 2 shared
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Last updated September 24, 2026