Coding work
Code generation, repair, and software-engineering tasks
Not enough matched evidence
Nemotron 3.5 Super VL 120B A12B is not ranked on the public lane for coding, so no winner is named for coding.
Confidence: limited
Nemotron 3.5 Super VL 120B A12B vs Quasar 438B
Updated October 15, 2026. Rank says Nemotron 3.5 Super VL 120B A12B 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
Nemotron 3.5 Super VL 120B A12B has the higher public point estimate, 49.51 versus 48.48. Their conditional score ranges overlap. These ranges do not establish rank confidence. 1 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.
Model A
NVIDIA
49.51/100
Estimated · Public rank #97
Conditional range 35.2–63.9
Model B
Multiverse Computing
48.48/100
Estimated · Public rank #104
Conditional range 34.1–62.8
- Shared results
- 1
- Nemotron 3.5 Super VL 120B A12B only
- 18
- Quasar 438B only
- 1
- Like-for-like categories
- 0 / 8
Estimated: Nemotron 3.5 Super VL 120B A12B and Quasar 438B. 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
Nemotron 3.5 Super VL 120B A12B and Quasar 438B are scored on Estimated evidence for agentic, so the reading is directional rather than like-for-like.
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.
—Nemotron 3.5 Super VL 120B A12B41.2Quasar 438B
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.
18 Nemotron 3.5 Super VL 120B A12B only
1 Shared
1 Quasar 438B 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.
A shared-evidence shape is not available.
BenchLM does not draw a radar or infer missing axes when the matched evidence is too sparse.
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
Directional only- Nemotron 3.5 Super VL 120B A12B
- 44.2
- Estimated · #61/127
- Quasar 438B
- 40.1
- Estimated · #67/127
- Basis
- BenchAlign v5.8 lane · 4 vs 1 public rows
- Reading
- Directional only
Knowledge
Directional only- Nemotron 3.5 Super VL 120B A12B
- 51.8
- Estimated · #73/184
- Quasar 438B
- 46.6
- Estimated · #92/184
- Basis
- BenchAlign v5.8 lane · 3 vs 0 public rows
- Reading
- Directional only
Coding
Not comparable- Nemotron 3.5 Super VL 120B A12B
- Not ranked
- Quasar 438B
- 41.2
- Estimated · #63/150
- Basis
- BenchAlign v5.8 lane · 4 vs 1 public rows
- Reading
- Not comparable
Reasoning
Not comparable- Nemotron 3.5 Super VL 120B A12B
- 73.0
- Unranked · 2 rankable rows
- Quasar 438B
- 78.3
- Unranked · 2 rankable rows
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Multimodal
Not comparable- Nemotron 3.5 Super VL 120B A12B
- 62.0
- Unranked · 5 rankable rows
- Quasar 438B
- Not ranked
- Basis
- Provisional lane · 1 vs 0 weighted rows
- Reading
- Not comparable
Multilingual
Not comparable- Nemotron 3.5 Super VL 120B A12B
- Not ranked
- Quasar 438B
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Instruction following
Not comparable- Nemotron 3.5 Super VL 120B A12B
- 66.6
- #72/146
- Quasar 438B
- Not ranked
- Basis
- Provisional lane · 1 vs 0 weighted rows
- Reading
- Not comparable
Math
Not comparable- Nemotron 3.5 Super VL 120B A12B
- Not ranked
- Quasar 438B
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
| Category | Nemotron 3.5 Super VL 120B A12B | Quasar 438B | Basis | Reading |
|---|---|---|---|---|
| Agentic | 44.2Estimated · #61/127 | 40.1Estimated · #67/127 | Directional onlyBenchAlign v5.8 lane · 4 vs 1 public rows | Directional only |
| Knowledge | 51.8Estimated · #73/184 | 46.6Estimated · #92/184 | Directional onlyBenchAlign v5.8 lane · 3 vs 0 public rows | Directional only |
| Coding | Not ranked | 41.2Estimated · #63/150 | Not comparableBenchAlign v5.8 lane · 4 vs 1 public rows | Not comparable |
| Reasoning | 73.0Unranked · 2 rankable rows | 78.3Unranked · 2 rankable rows | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Multimodal | 62.0Unranked · 5 rankable rows | Not ranked | Not comparableProvisional lane · 1 vs 0 weighted rows | Not comparable |
| Multilingual | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Instruction following | 66.6#72/146 | Not ranked | Not comparableProvisional lane · 1 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 v5.8) 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.
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
- Nemotron 3.5 Super VL 120B A12B
- API rate not published
- Fits in one request
- Quasar 438B
- $0.0015
- Fits in one request
Nemotron 3.5 Super VL 120B A12B has no comparable published API token rate.
Repository review
50K fresh input + 3K output tokens
- Nemotron 3.5 Super VL 120B A12B
- API rate not published
- Fits in one request
- Quasar 438B
- $0.0354
- Fits in one request
Nemotron 3.5 Super VL 120B A12B has no comparable published API token rate.
Cache-heavy agent loop
200K cached + 20K fresh input + 10K output tokens
- Nemotron 3.5 Super VL 120B A12B
- API rate not published
- Fits in one request
- Cached-input rate unavailable
- Quasar 438B
- $0.15
- Fits in one request
- Cached input priced at the published list-input rate
Quasar 438B has no published cached-input rate, so cached tokens use its listed input rate. Nemotron 3.5 Super VL 120B A12B 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.
SpecificationNemotron 3.5 Super VL 120B A12BQuasar 438B
Context window
Maximum documented context; output-token limits may be lower.
Nemotron 3.5 Super VL 120B A12B
Quasar 438B
API model ID
Nemotron 3.5 Super VL 120B A12B
Not sourced
Quasar 438B
quasar-438b
CompactifAI Quasar 438B documentationCached-input rate
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
Nemotron 3.5 Super VL 120B A12B
No comparable hosted API rate
NVIDIA Hugging Face model cardQuasar 438B
Not published
CompactifAI API pricingDocumented inputs
Nemotron 3.5 Super VL 120B A12B
text, image, video
NVIDIA BF16 model cardQuasar 438B
Not sourced
Documented outputs
Nemotron 3.5 Super VL 120B A12B
Quasar 438B
Not sourced
Provider availability
Nemotron 3.5 Super VL 120B A12B
Open Weights · Hugging Face, self-hosted inference
NVIDIA BF16 model cardQuasar 438B
Generally Available · CompactifAI API
CompactifAI Quasar 438B documentationReasoning profile
Nemotron 3.5 Super VL 120B A12B
Reasoning
Quasar 438B
Reasoning
Weight access
Nemotron 3.5 Super VL 120B A12B
Open Weight
Quasar 438B
Proprietary
License
Nemotron 3.5 Super VL 120B A12B
Open Weight
Quasar 438B
Proprietary
Release date
Nemotron 3.5 Super VL 120B A12B
2026-10-15
Quasar 438B
2026-09-02
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
- Nemotron 3.5 Super VL 120B A12B has the higher public point estimate, 49.51 versus 48.48. Their conditional score ranges overlap. These ranges do not establish rank confidence.
- 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, Nemotron 3.5 Super VL 120B A12B or Quasar 438B?
Nemotron 3.5 Super VL 120B A12B has the higher public point estimate, 49.51 versus 48.48. Their conditional score ranges overlap. These ranges do not establish rank confidence. The page therefore keeps the decision tied to the specific documented workload.
Which is better for coding, Nemotron 3.5 Super VL 120B A12B or Quasar 438B?
Nemotron 3.5 Super VL 120B A12B is not ranked on the public lane for coding, so no winner is named for coding.
Which is better for agentic tasks, Nemotron 3.5 Super VL 120B A12B or Quasar 438B?
Nemotron 3.5 Super VL 120B A12B scores higher for agentic tasks on the public lane, 44.2 to 40.1. Nemotron 3.5 Super VL 120B A12B and Quasar 438B are scored on Estimated evidence for agentic tasks, so the reading is directional rather than like-for-like. BenchLM does not name a winner for agentic tasks from a directional reading; read the shared benchmark rows directly and test the models on the same task set.
Which costs less, Nemotron 3.5 Super VL 120B A12B or Quasar 438B?
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, Nemotron 3.5 Super VL 120B A12B or Quasar 438B?
Both models list the same context window, 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 evidence20 rows
Agentic
Terminal-Bench 2.1
Nemotron 3.5 Super VL 120B A12B66.7%SourceQuasar 438B69.3%SourceQuasar 438B leads this result
τ²-bench Airline
Nemotron 3.5 Super VL 120B A12B76.5%SourceQuasar 438B—Not directly comparable
τ³-bench results
Nemotron 3.5 Super VL 120B A12B18.9%SourceQuasar 438B—Not directly comparable
BrowseComp
Nemotron 3.5 Super VL 120B A12B78%SourceQuasar 438B—Not directly comparable
Coding
LiveCodeBench v6
Nemotron 3.5 Super VL 120B A12B88.2%SourceQuasar 438B—Not directly comparable
SWE-bench Verified
Nemotron 3.5 Super VL 120B A12B71.1%SourceQuasar 438B—Not directly comparable
SWE Multilingual
Nemotron 3.5 Super VL 120B A12B67.7%SourceQuasar 438B—Not directly comparable
SWE-bench Pro
Nemotron 3.5 Super VL 120B A12B51.8%SourceQuasar 438B—Not directly comparable
Terminal-Bench 2.1
Nemotron 3.5 Super VL 120B A12B—Quasar 438B69.3%SourceNot directly comparable
Reasoning
CritPt
Nemotron 3.5 Super VL 120B A12B10.9%SourceQuasar 438B—Not directly comparable
Multimodal
BabyVision
Nemotron 3.5 Super VL 120B A12B29.6%SourceQuasar 438B—Not directly comparable
MMLongBench-Doc
Nemotron 3.5 Super VL 120B A12B62.8%SourceQuasar 438B—Not directly comparable
V*
Nemotron 3.5 Super VL 120B A12B85.6%SourceQuasar 438B—Not directly comparable
MathVision
Nemotron 3.5 Super VL 120B A12B78.2%SourceQuasar 438B—Not directly comparable
CharXiv
Nemotron 3.5 Super VL 120B A12B80.8%SourceQuasar 438B—Not directly comparable
Knowledge
Instruction following
IFBench
Nemotron 3.5 Super VL 120B A12B70.9%SourceQuasar 438B—Not directly comparable
Math
Apex Shortlist
Nemotron 3.5 Super VL 120B A12B88.4%SourceQuasar 438B—Not directly comparable
20 public results · 1 shared
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Last updated October 15, 2026