Ember-1 vs Nemotron 3.5 Super VL
Nemotron 3.5 Super VL costs 30.0x less per output token than Ember-1 ($0.50 vs $15.00 per million). Updated October 22, 2026; no benchmark has tested both models yet.
- Coding
- 52.6
- Overall
- No data
- Output $/M
- $15.00
- Coding
- No data
- Overall
- 35.6
- Output $/M
- $0.50
Ember-1 or Nemotron 3.5 Super VL: which to pick
Only Ember-1 has a coding score, 52.6 on the Vibe Coding Index; Nemotron 3.5 Super VL has none, so the two cannot be ranked on coding.
Pick Nemotron 3.5 Super VL for output tokens 30.0x cheaper ($0.50 vs $15.00 per million).
No benchmark has tested both yet. Ember-1 has results on Terminal-Bench 4 (Vals AI), Vibe Code Bench (Vals AI) and Code migration (Vals AI); Nemotron 3.5 Super VL on LiveBench coding, SciCode and AA Intelligence Index. Compare them on price and context instead.
Which one for your work
Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.
Coding
Vibe Coding Index, six public coding benchmarks
No call
Only Ember-1 has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
No call
Only Nemotron 3.5 Super VL has a AA Intelligence Index result, 26.5.
Directional only
Web design
Design Arena: websites
No call
Only Nemotron 3.5 Super VL has a Design Arena: websites result, 1173.
Directional only
Long documents
Listed context window
No call
Both take 1.05M tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Nemotron 3.5 Super VL
Ember-1 $0.011, Nemotron 3.5 Super VL $0.0004 per turn.
List prices
At a glance
- Coding index
- Ember-1 52.6 from 2 benchmarks, Nemotron 3.5 Super VL not benchmarked.
- Widest category
- None yet: no category has been tested on both models.
- Widest single gap
- None yet: no benchmark has tested both models.
- Output price
- Ember-1 $15.00 against Nemotron 3.5 Super VL $0.50 per million output tokens, 30.0x apart.
- Context window
- Both take 1.05M tokens.
Benchmark by benchmark
Every board either model has a result on, a category to a fold; bars are each result on a 0 to 100 scale. Only one model is measured on each, so no row names a leader.
CodingDirectional onlySix of these boards feed the Vibe Coding Index7 boards measured
| Benchmark | Ember-1 | Nemotron 3.5 Super VL | Leader |
|---|---|---|---|
| LiveBench coding | Not measured | 65.5% | Only Nemotron 3.5 Super VL measured |
| Terminal-Bench 4 (Vals AI) | 20.7% | Not measured | Only Ember-1 measured |
| Vibe Code Bench (Vals AI) | 83.9% | Not measured | Only Ember-1 measured |
| Code migration (Vals AI) | 32.5% | Not measured | Only Ember-1 measured |
| IOI (Vals AI) | 46.3% | Not measured | Only Ember-1 measured |
| CyberBench (Vals AI) | 69.5% | Not measured | Only Ember-1 measured |
| SciCode | Not measured | 47.8% | Only Nemotron 3.5 Super VL measured |
| Neither model has a result on the other 36 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | Ember-1 | Nemotron 3.5 Super VL | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 26.5 | Only Nemotron 3.5 Super VL measured |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index10 boards measured
| Benchmark | Ember-1 | Nemotron 3.5 Super VL | Leader |
|---|---|---|---|
| LiveBench research | Not measured | 70.9% | Only Nemotron 3.5 Super VL measured |
| LiveBench browser | Not measured | 4.0% | Only Nemotron 3.5 Super VL measured |
| LiveBench long agentic | Not measured | 15.8% | Only Nemotron 3.5 Super VL measured |
| Finance Agent (Vals AI) | 51.8% | Not measured | Only Ember-1 measured |
| Tax Agent Bench (Vals AI) | 31.1% | Not measured | Only Ember-1 measured |
| Legal Research Bench (Vals AI) | 44.7% | Not measured | Only Ember-1 measured |
| Excel Modeling Benchmark (Vals AI) | 63.4% | Not measured | Only Ember-1 measured |
| BioMysteryBench (Vals AI) | 67.0% | Not measured | Only Ember-1 measured |
| Terminal-Bench-Science (Vals AI) | 5.7% | Not measured | Only Ember-1 measured |
| Vals Science Index | 31.8% | Not measured | Only Ember-1 measured |
| Neither model has a result on the other 32 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index3 boards measured
| Benchmark | Ember-1 | Nemotron 3.5 Super VL | Leader |
|---|---|---|---|
| LiveBench reasoning | Not measured | 78.8% | Only Nemotron 3.5 Super VL measured |
| MysteryMechanism (Vals AI) | 22.5% | Not measured | Only Ember-1 measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 30.7% | Only Nemotron 3.5 Super VL measured |
| Neither model has a result on the other 20 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index6 boards measured
| Benchmark | Ember-1 | Nemotron 3.5 Super VL | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1173 | Only Nemotron 3.5 Super VL measured |
| Design Arena: UI components | Not measured | 1149 | Only Nemotron 3.5 Super VL measured |
| Design Arena: game dev | Not measured | 1110 | Only Nemotron 3.5 Super VL measured |
| Design Arena: 3D | Not measured | 1128 | Only Nemotron 3.5 Super VL measured |
| Design Arena: all code categories | Not measured | 1154 | Only Nemotron 3.5 Super VL measured |
| LiveBench design | Not measured | 60.7% | Only Nemotron 3.5 Super VL measured |
| Neither model has a result on the other 3 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index3 boards measured
| Benchmark | Ember-1 | Nemotron 3.5 Super VL | Leader |
|---|---|---|---|
| LiveBench data analysis | Not measured | 64.6% | Only Nemotron 3.5 Super VL measured |
| Public Benefits Bench (Vals AI) | 66.2% | Not measured | Only Ember-1 measured |
| Long context reasoning (AA-LCR) | Not measured | 69.0% | Only Nemotron 3.5 Super VL measured |
| Neither model has a result on the other 45 boards here | |||
What each workload costs
Three fixed token mixes at each model's listed price, so per-token rates become a bill.
Chat turn
1K input + 500 output tokens
Nemotron 3.5 Super VL costs less
Repository review
50K input + 3K output tokens
Nemotron 3.5 Super VL costs less
Agent loop
200K input + 10K output tokens
Nemotron 3.5 Super VL costs less
Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.
Specification differences
The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.
| Specification | Fireworks Ember-1 | NVIDIA Nemotron 3.5 Super VL |
|---|---|---|
| Maker | Fireworks | NVIDIA |
| Weights | No public weights listed | Open weights |
| Released | September 24, 2026 | October 15, 2026 |
| Context window | 1.05M | 1.05M |
| Input $/Mtok | $3.00 | $0.15 |
| Output $/Mtok | $15.00 | $0.50 |
| Coding index | 52.6 | Not benchmarked |
| Independent measurements behind it | 2 | 1 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Ember-1 better than Nemotron 3.5 Super VL for coding?
Only Ember-1 has a coding score, 52.6 on the Vibe Coding Index; Nemotron 3.5 Super VL has none, so the two cannot be ranked on coding. Pick Nemotron 3.5 Super VL for output tokens 30.0x cheaper ($0.50 vs $15.00 per million).
Which is cheaper, Ember-1 or Nemotron 3.5 Super VL?
Ember-1 costs $3.00 per million input tokens and $15.00 per million output tokens; Nemotron 3.5 Super VL costs $0.15 and $0.50. Cost per solved task is known for neither of them.
Which has the bigger context window, Ember-1 or Nemotron 3.5 Super VL?
Neither: both take 1.05M tokens.
Has any benchmark tested both Ember-1 and Nemotron 3.5 Super VL?
No benchmark has tested both yet. Ember-1 has results on Terminal-Bench 4 (Vals AI), Vibe Code Bench (Vals AI) and Code migration (Vals AI); Nemotron 3.5 Super VL on LiveBench coding, SciCode and AA Intelligence Index. Compare them on price and context instead. Data as of October 22, 2026.