Long documents
Prompts that approach the documented context limit
GPT-5.6 Sol
GPT-5.6 Sol has the larger documented context window.
Confidence: documented
GPT-5.6 Sol vs Nemotron 3 Nano Omni 30B A3B
Updated September 24, 2026. Rank says GPT-5.6 Sol 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-5.6 Sol has the higher public score, 78.49 versus 30.84, 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
30.84/100
Estimated · Public rank #153
90% interval 19.3–42.4
- Shared results
- 2
- GPT-5.6 Sol only
- 35
- Nemotron 3 Nano Omni 30B A3B only
- 14
- Like-for-like categories
- 1 / 8
Supported: GPT-5.6 Sol · Estimated: Nemotron 3 Nano Omni 30B A3BHow 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
Nemotron 3 Nano Omni 30B A3B 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
Nemotron 3 Nano Omni 30B A3B 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: listed-ratesRepository 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.
71.6GPT-5.6 Sol20.7Nemotron 3 Nano Omni 30B A3B
Directional only · BenchAlign v5.7
GPT-5.6 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.
35 GPT-5.6 Sol only
2 Shared
14 Nemotron 3 Nano Omni 30B A3B only
3 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.
GPQAKnowledge
Normalized gap 22.4GPT-5.6 Sol:94.6%Nemotron 3 Nano Omni 30B A3B:72.2%
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.
Knowledge
Like-for-like- GPT-5.6 Sol
- 78.8
- Supported · #7/158
- Nemotron 3 Nano Omni 30B A3B
- 31.9
- Supported · #121/158
- Basis
- BenchAlign v5.7 lane · 8 vs 3 public rows
- Reading
- GPT-5.6 Sol leads
Coding
Directional only- GPT-5.6 Sol
- 71.6
- Supported · #6/135
- Nemotron 3 Nano Omni 30B A3B
- 20.7
- Estimated · #114/135
- Basis
- BenchAlign v5.7 lane · 12 vs 2 public rows
- Reading
- Directional only
Multimodal
Directional only- GPT-5.6 Sol
- 87.6
- #5/50
- Nemotron 3 Nano Omni 30B A3B
- 39.3
- #44/50
- Basis
- Provisional lane · 1 vs 1 weighted rows
- Reading
- Directional only
Instruction following
Directional only- GPT-5.6 Sol
- 87.7
- #28/124
- Nemotron 3 Nano Omni 30B A3B
- 72.4
- #62/124
- Basis
- Provisional lane · 0 vs 1 weighted rows
- Reading
- Directional only
Agentic
Not comparable- GPT-5.6 Sol
- 69.6
- Supported · #7/105
- Nemotron 3 Nano Omni 30B A3B
- Not ranked
- Basis
- BenchAlign v5.7 lane · 9 vs 2 public rows
- Reading
- Not comparable
Reasoning
Not comparable- GPT-5.6 Sol
- 72.1
- #8/19
- Nemotron 3 Nano Omni 30B A3B
- 49.4
- Unranked · 2 rankable rows
- Basis
- Provisional lane · 2 vs 0 weighted rows
- Reading
- Not comparable
Multilingual
Not comparable- GPT-5.6 Sol
- Not ranked
- Nemotron 3 Nano Omni 30B A3B
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Math
Not comparable- GPT-5.6 Sol
- 96.8
- Unranked · 3 rankable rows
- Nemotron 3 Nano Omni 30B A3B
- Not ranked
- Basis
- Provisional lane · 2 vs 0 weighted rows
- Reading
- Not comparable
| Category | GPT-5.6 Sol | Nemotron 3 Nano Omni 30B A3B | Basis | Reading |
|---|---|---|---|---|
| Knowledge | 78.8Supported · #7/158 | 31.9Supported · #121/158 | Like-for-likeBenchAlign v5.7 lane · 8 vs 3 public rows | GPT-5.6 Sol leads |
| Coding | 71.6Supported · #6/135 | 20.7Estimated · #114/135 | Directional onlyBenchAlign v5.7 lane · 12 vs 2 public rows | Directional only |
| Multimodal | 87.6#5/50 | 39.3#44/50 | Directional onlyProvisional lane · 1 vs 1 weighted rows | Directional only |
| Instruction following | 87.7#28/124 | 72.4#62/124 | Directional onlyProvisional lane · 0 vs 1 weighted rows | Directional only |
| Agentic | 69.6Supported · #7/105 | Not ranked | Not comparableBenchAlign v5.7 lane · 9 vs 2 public rows | Not comparable |
| Reasoning | 72.1#8/19 | 49.4Unranked · 2 rankable rows | Not comparableProvisional lane · 2 vs 0 weighted rows | Not comparable |
| Multilingual | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Math | 96.8Unranked · 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.
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-5.6 Sol
- $0.014
- Fits in one request
- Nemotron 3 Nano Omni 30B A3B
- Self-hosted; infrastructure cost varies
- Fits in one request
Nemotron 3 Nano Omni 30B A3B has no comparable published API token rate.
Repository review
50K fresh input + 3K output tokens
- GPT-5.6 Sol
- $0.26
- Fits in one request
- Nemotron 3 Nano Omni 30B A3B
- Self-hosted; infrastructure cost varies
- Fits in one request
Nemotron 3 Nano Omni 30B A3B has no comparable published API token rate.
Cache-heavy agent loop
200K cached + 20K fresh input + 10K output tokens
- GPT-5.6 Sol
- $0.36
- Fits in one request
- Nemotron 3 Nano Omni 30B A3B
- Self-hosted; infrastructure cost varies
- Fits in one request
- Cached-input rate unavailable
Nemotron 3 Nano Omni 30B A3B 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-5.6 SolNemotron 3 Nano Omni 30B A3B
Context window
Maximum documented context; output-token limits may be lower.
GPT-5.6 Sol
1.05M
OpenAI model catalogNemotron 3 Nano Omni 30B A3B
256K
API model ID
GPT-5.6 Sol
gpt-5.6-sol
OpenAI model catalogNemotron 3 Nano Omni 30B A3B
Not sourced
Cached-input rate
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
GPT-5.6 Sol
$0.4 per 1M cached input tokens
OpenAI pricingNemotron 3 Nano Omni 30B A3B
No comparable hosted API rate
Documented inputs
GPT-5.6 Sol
text, image
OpenAI model catalogNemotron 3 Nano Omni 30B A3B
Not sourced
Documented outputs
GPT-5.6 Sol
Nemotron 3 Nano Omni 30B A3B
Not sourced
Provider availability
GPT-5.6 Sol
Generally Available · OpenAI Responses API
OpenAI model catalogNemotron 3 Nano Omni 30B A3B
Not sourced
Reasoning profile
GPT-5.6 Sol
Reasoning
Nemotron 3 Nano Omni 30B A3B
Reasoning
Weight access
GPT-5.6 Sol
Proprietary
Nemotron 3 Nano Omni 30B A3B
Open Weight
License
GPT-5.6 Sol
Proprietary
Nemotron 3 Nano Omni 30B A3B
Open Weight
Release date
GPT-5.6 Sol
2026-07-09
Nemotron 3 Nano Omni 30B A3B
2026-04-28
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-5.6 Sol has the higher public score, 78.49 versus 30.84, 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-5.6 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-5.6 Sol or Nemotron 3 Nano Omni 30B A3B?
GPT-5.6 Sol has the higher public score, 78.49 versus 30.84, 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-5.6 Sol or Nemotron 3 Nano Omni 30B A3B?
GPT-5.6 Sol scores higher for coding on the public lane, 71.6 to 20.7. Nemotron 3 Nano Omni 30B A3B 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-5.6 Sol or Nemotron 3 Nano Omni 30B A3B?
Nemotron 3 Nano Omni 30B A3B is not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.
Which costs less, GPT-5.6 Sol or Nemotron 3 Nano Omni 30B A3B?
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-5.6 Sol or Nemotron 3 Nano Omni 30B A3B?
GPT-5.6 Sol has the larger documented context window: 1.05M, compared with 256K.
Benchmark evidence
The full public result ledger is available for audit without forcing a wide desktop table onto a phone.
Browse raw public benchmark evidence51 rows
Agentic
Terminal-Bench 3.0
GPT-5.6 Sol34.6%SourceNemotron 3 Nano Omni 30B A3B—Not directly comparable
Terminal-Bench 2.1
GPT-5.6 Sol91.9%SourceNemotron 3 Nano Omni 30B A3B—Not directly comparable
BrowseComp
GPT-5.6 Sol92.2%SourceNemotron 3 Nano Omni 30B A3B—Not directly comparable
OSWorld 2.0
GPT-5.6 Sol62.6%SourceNemotron 3 Nano Omni 30B A3B—Not directly comparable
CyberGym
GPT-5.6 Sol84.5%SourceNemotron 3 Nano Omni 30B A3B—Not directly comparable
ExploitGym
GPT-5.6 Sol33.7%SourceNemotron 3 Nano Omni 30B A3B—Not directly comparable
Toolathlon
GPT-5.6 Sol58%SourceNemotron 3 Nano Omni 30B A3B—Not directly comparable
Terminal-Bench 2.1 (Vals)
GPT-5.6 Sol85.8%SourceNemotron 3 Nano Omni 30B A3B—Not directly comparable
ApprenticeBench
GPT-5.6 Sol26%SourceNemotron 3 Nano Omni 30B A3B—Not directly comparable
OSWorld
GPT-5.6 Sol—Nemotron 3 Nano Omni 30B A3B47.4%SourceNot directly comparable
τ²-bench results
GPT-5.6 Sol—Nemotron 3 Nano Omni 30B A3B45.3%SourceNot directly comparable
Coding
Bug Hunt Bench
GPT-5.6 Sol42 fixesSourceNemotron 3 Nano Omni 30B A3B—Not directly comparable
SWE-bench Pro
GPT-5.6 Sol64.6%SourceNemotron 3 Nano Omni 30B A3B—Not directly comparable
Terminal-Bench 2.1
GPT-5.6 Sol91.9%SourceNemotron 3 Nano Omni 30B A3B—Not directly comparable
DeepSWE
GPT-5.6 Sol72.7%SourceNemotron 3 Nano Omni 30B A3B—Not directly comparable
FrontierCode 1.1 Extended
GPT-5.6 Sol60.6%SourceNemotron 3 Nano Omni 30B A3B—Not directly comparable
FrontierSWE v2
GPT-5.6 Sol32.2%SourceNemotron 3 Nano Omni 30B A3B—Not directly comparable
cursorBench32
GPT-5.6 Sol67.2%SourceNemotron 3 Nano Omni 30B A3B—Not directly comparable
VulcanBench v3
GPT-5.6 Sol87.0%SourceNemotron 3 Nano Omni 30B A3B—Not directly comparable
VulcanBench CII v1
GPT-5.6 Sol86.5%SourceNemotron 3 Nano Omni 30B A3B—Not directly comparable
LiveCodeBench (Vals)
GPT-5.6 Sol82.6%SourceNemotron 3 Nano Omni 30B A3B—Not directly comparable
SWE-bench (Vals)
GPT-5.6 Sol96.2%SourceNemotron 3 Nano Omni 30B A3B—Not directly comparable
cursorBench40
GPT-5.6 Sol41.7%SourceNemotron 3 Nano Omni 30B A3B—Not directly comparable
LiveCodeBench v5
GPT-5.6 Sol—Nemotron 3 Nano Omni 30B A3B63.2%SourceNot directly comparable
SciCode
GPT-5.6 Sol—Nemotron 3 Nano Omni 30B A3B32%SourceNot directly comparable
Reasoning
Multimodal
MMMU-Pro
GPT-5.6 Sol83%SourceNemotron 3 Nano Omni 30B A3B—Not directly comparable
MMMU-Pro w/ Python
GPT-5.6 Sol84.6%SourceNemotron 3 Nano Omni 30B A3B—Not directly comparable
MMMU
GPT-5.6 Sol—Nemotron 3 Nano Omni 30B A3B70.8%SourceNot directly comparable
MMLongBench-Doc
GPT-5.6 Sol—Nemotron 3 Nano Omni 30B A3B57.5%SourceNot directly comparable
CharXiv
GPT-5.6 Sol—Nemotron 3 Nano Omni 30B A3B76.3%SourceNot directly comparable
ScreenSpot Pro
GPT-5.6 Sol—Nemotron 3 Nano Omni 30B A3B57.8%SourceNot directly comparable
Video-MME (w/o subtitle)
GPT-5.6 Sol—Nemotron 3 Nano Omni 30B A3B72.2%SourceNot directly comparable
AI2D_TEST
GPT-5.6 Sol—Nemotron 3 Nano Omni 30B A3B88.5%SourceNot directly comparable
RefCOCO (avg)
GPT-5.6 Sol—Nemotron 3 Nano Omni 30B A3B90.5%SourceNot directly comparable
Knowledge
GPQA
GPT-5.6 Sol94.6%SourceNemotron 3 Nano Omni 30B A3B72.2%SourceGPT-5.6 Sol leads this result
GPQA-D
GPT-5.6 Sol94.6%SourceNemotron 3 Nano Omni 30B A3B72.2%SourceGPT-5.6 Sol leads this result
HLE-Verified
GPT-5.6 Sol54.5%SourceNemotron 3 Nano Omni 30B A3B—Not directly comparable
LABBench2
GPT-5.6 Sol82.1%SourceNemotron 3 Nano Omni 30B A3B—Not directly comparable
HealthBench Professional
GPT-5.6 Sol60.5%SourceNemotron 3 Nano Omni 30B A3B—Not directly comparable
HealthBench Hard
GPT-5.6 Sol33.1%SourceNemotron 3 Nano Omni 30B A3B—Not directly comparable
GPQA Diamond (Vals)
GPT-5.6 Sol95.2%SourceNemotron 3 Nano Omni 30B A3B—Not directly comparable
MMLU-Pro (Vals)
GPT-5.6 Sol89.1%SourceNemotron 3 Nano Omni 30B A3B—Not directly comparable
MMLU-Pro
GPT-5.6 Sol—Nemotron 3 Nano Omni 30B A3B77.3%SourceNot directly comparable
Instruction following
IFBench
GPT-5.6 Sol—Nemotron 3 Nano Omni 30B A3B74.2%SourceNot directly comparable
Math
FrontierMath (legacy)
GPT-5.6 Sol89%SourceNemotron 3 Nano Omni 30B A3B—Not directly comparable
FrontierMath v2 (Tiers 1-3)
GPT-5.6 Sol89.000%SourceNemotron 3 Nano Omni 30B A3B—Not directly comparable
FrontierMath v2 (Tier 4)
GPT-5.6 Sol83.000%SourceNemotron 3 Nano Omni 30B A3B—Not directly comparable
AIME 2025
GPT-5.6 Sol—Nemotron 3 Nano Omni 30B A3B82.1%SourceNot directly comparable
51 public results · 2 shared
Watch GPT-5.6 Sol vs Nemotron 3 Nano Omni 30B A3B
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Last updated September 24, 2026