// alternatives · October 2026
Nemotron 3.5 Super VL alternatives
Cheaper models that come close, budget substitutes, and the cheapest step up — chosen on published LiveBench scores and live list price, never on our opinion. Every model here supports tool calling and image input, as Nemotron 3.5 Super VL does.
The closest cheaper alternative to Nemotron 3.5 Super VL is Claude Haiku 5.5 — 19.6 points higher overall, 16% cheaper on LiveBench and list price.
Nemotron 3.5 Super VL: 50.2 overall on LiveBench, $0.237 per 1M blended tokens, about $98.00/mo for a RAG assistant.
Cheaper, close in quality
Lower list price and within 5 points of Nemotron 3.5 Super VL on LiveBench overall — the switches least likely to be noticed by users. Strongest first.
| Model | Overall | vs Nemotron 3.5 Super VL | Blended / 1M | RAG assistant | Context |
|---|---|---|---|---|---|
| Claude Haiku 5.5anthropic 19.6 points higher overall, 16% cheaper. Head to head → | 69.8 | +19.6 | $0.200−16% | $74.00/mo | 1M |
| GPT-6 Lunaopenai 14.4 points higher overall, 16% cheaper. Head to head → | 64.6 | +14.4 | $0.200−16% | $74.00/mo | 1.1M |
Match it on one task for less
For each LiveBench category, the cheapest model that scores at least as well as Nemotron 3.5 Super VL there. Useful when your workload is mostly one kind of task.
| Category | Cheapest match | Score | Blended / 1M |
|---|---|---|---|
| Long-horizon agentic | Claude Haiku 5.5 | 40.0 vs 11.7 | $0.200−16% |
| Coding | Claude Haiku 5.5 | 91.4 vs 71.3 | $0.200−16% |
| Reasoning | Claude Haiku 5.5 | 82.4 vs 74.6 | $0.200−16% |
| Browser | Claude Haiku 5.5 | 69.5 vs 21.6 | $0.200−16% |
| Data analysis | GPT-6 Luna | 73.4 vs 64.6 | $0.200−16% |
| Research | Claude Haiku 5.5 | 81.9 vs 66.7 | $0.200−16% |
| Documents & design | Claude Haiku 5.5 | 83.1 vs 62.8 | $0.200−16% |
Stronger options, cheapest first
Models that beat Nemotron 3.5 Super VL on LiveBench overall, ordered by what the upgrade costs.
| Model | Overall | vs Nemotron 3.5 Super VL | Blended / 1M | RAG assistant | Context |
|---|---|---|---|---|---|
| Claude Haiku 5.5anthropic 19.6 points higher overall, 16% cheaper. Head to head → | 69.8 | +19.6 | $0.200−16% | $74.00/mo | 1M |
| GPT-6 Lunaopenai 14.4 points higher overall, 16% cheaper. Head to head → | 64.6 | +14.4 | $0.200−16% | $74.00/mo | 1.1M |
| GLM 5.3 Flashz-ai 11.8 points higher overall, the same list price. Head to head → | 62.1 | +11.8 | $0.237 | $102.00/mo | 1.0M |
| MiniMax M3.1 Flashminimax 16.7 points higher overall, 11% more expensive. Head to head → | 66.9 | +16.7 | $0.262 | $102.00/mo | 1.0M |
| Qwen3.8 27Bqwen 8.2 points higher overall, 44% more expensive. Head to head → | 58.4 | +8.2 | $0.342 | $92.16/mo | 1M |
Nemotron 3.5 Super VL alternatives FAQ
What is the best alternative to Nemotron 3.5 Super VL?
Claude Haiku 5.5. 19.6 points higher overall, 16% cheaper. Every suggestion supports tool calling and image input, like Nemotron 3.5 Super VL.
What is the cheapest alternative to Nemotron 3.5 Super VL?
Claude Haiku 5.5 at $0.200 per 1M blended tokens, scoring 69.8 overall against Nemotron 3.5 Super VL's 50.2. On a RAG assistant at 100K requests a month that is $74.00 instead of $98.00.
Which model is better than Nemotron 3.5 Super VL?
The cheapest model that scores higher overall on LiveBench is Claude Haiku 5.5 — 19.6 points higher overall, 16% cheaper.
Is there a cheaper model that matches Nemotron 3.5 Super VL on specific tasks?
Yes, in 7 of the seven LiveBench categories. For example, long-horizon agentic: Claude Haiku 5.5 (40.0 vs 11.7); coding: Claude Haiku 5.5 (91.4 vs 71.3); reasoning: Claude Haiku 5.5 (82.4 vs 74.6).
How alternatives are chosen
- Scores — LiveBench release 2026-10-25. Only models with a published run are suggested on quality; a missing model means “not evaluated”, not “worse”.
- Prices — live list prices from OpenRouter, blended 3:1 input:output. Monthly figures price a RAG assistant with the published cached-input rate where there is one.
- Same job — suggestions must support every capability Nemotron 3.5 Super VL has among tool calling and image input. Other listings of the same model (free or batch tiers) are variants, not alternatives, and are left out.
A few points on a public benchmark can hide large differences on your own tasks. Shortlist here, then decide with an eval — how to build one.