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Llama-3.3-Nemotron-Super-49B-v1

nebius · chat model

Llama-3.3-Nemotron-Super-49B-v1 is listed here as a chat model from nebius. This page shows simple API pricing, token limits, and capability flags so you can compare it with similar options.

Input
$0.1000 / 1M tokens
Output
$0.4000 / 1M tokens
Cached input
N/A
Context
131.1K
Compare similar models Open a side-by-side table using this route and the closest match from the current catalog. Estimate workload cost Use token counts, request volume, and cache assumptions to check a realistic monthly bill. Explore benchmark family Review source-backed benchmark rows for the attached base model family. Check data sources See how pricing data is generated and what still needs provider verification.

Quick read

Best for

Use this page when you need a fast view of cost, context size, and supported features before testing the model in your own workload.

Things to verify

Always check the provider page for discounts, cache pricing, region rules, and any model limits that may not appear in public metadata.

Pricing

Item Price
Input
$0.1000 / 1M tokens
Output
$0.4000 / 1M tokens
Embedding
$0.1000 / 1M tokens

Token limits

Context window
131.1K
Max input tokens
131.1K
Max output tokens
131.1K
Max tokens
131.1K

Capabilities

Capability Supported
Vision —
Function calling ✅
Parallel function calling —
Tool choice —
Prompt caching —
Reasoning —
Response schema —
System messages —
Audio input —
Audio output —
Web search —
PDF input —
Video input —

Benchmarks

Most benchmark rows are attached to the base model family rather than this provider route. Open benchmark explorer

Benchmark Score Metric Scope Checked Source
MMLU (CoT) 86.0 macro_avg/acc Base model: Llama 3.3 (Llama-3.3 70B Instruct) 2026-05-31 Link
MMLU-Pro (CoT) 68.9 macro_avg/acc Base model: Llama 3.3 (Llama-3.3 70B Instruct) 2026-05-31 Link
GPQA Diamond 50.5 acc Base model: Llama 3.3 (Llama-3.3 70B Instruct) 2026-05-31 Link
HumanEval 88.4 pass@1 Base model: Llama 3.3 (Llama-3.3 70B Instruct) 2026-05-31 Link
MATH (CoT) 77.0 sympy_intersection_score Base model: Llama 3.3 (Llama-3.3 70B Instruct) 2026-05-31 Link
MMLU (CoT) 86.0 macro_avg/acc Base model: Llama 3.3 (Llama-3.3 70B Instruct) 2026-05-31 Link
MMLU-Pro (CoT) 68.9 macro_avg/acc Base model: Llama 3.3 (Llama-3.3 70B Instruct) 2026-05-31 Link
IFEval 92.1 Base model: Llama 3.3 (Llama-3.3 70B Instruct) 2026-05-31 Link
HumanEval 88.4 pass@1 Base model: Llama 3.3 (Llama-3.3 70B Instruct) 2026-05-31 Link
MT-Bench 8.22 total Base model: Nemotron (Nemotron-4-340B-Instruct) 2026-05-31 Link
IFEval 79.9 Prompt-Strict Acc Base model: Nemotron (Nemotron-4-340B-Instruct) 2026-05-31 Link
IFEval 86.1 Instruction-Strict Acc Base model: Nemotron (Nemotron-4-340B-Instruct) 2026-05-31 Link
MMLU 78.7 0-shot Base model: Nemotron (Nemotron-4-340B-Instruct) 2026-05-31 Link
GSM8K 92.3 0-shot Base model: Nemotron (Nemotron-4-340B-Instruct) 2026-05-31 Link
HumanEval 73.2 0-shot Base model: Nemotron (Nemotron-4-340B-Instruct) 2026-05-31 Link
MBPP 75.4 0-shot Base model: Nemotron (Nemotron-4-340B-Instruct) 2026-05-31 Link
Arena Hard 54.2 Arena Hard Base model: Nemotron (Nemotron-4-340B-Instruct) 2026-05-31 Link
AlpacaEval 2.0 LC 41.5 Length Controlled Base model: Nemotron (Nemotron-4-340B-Instruct) 2026-05-31 Link
AIME 2025 76.25% Reasoning On Base model: Nemotron (NVIDIA-Nemotron-Nano-12B-v2) 2026-05-31 Link
MATH-500 97.75% Reasoning On Base model: Nemotron (NVIDIA-Nemotron-Nano-12B-v2) 2026-05-31 Link
GPQA 64.48% Reasoning On Base model: Nemotron (NVIDIA-Nemotron-Nano-12B-v2) 2026-05-31 Link
LCB 70.79% Reasoning On Base model: Nemotron (NVIDIA-Nemotron-Nano-12B-v2) 2026-05-31 Link
BFCL 66.98% Reasoning On Base model: Nemotron (NVIDIA-Nemotron-Nano-12B-v2) 2026-05-31 Link
IFEval Prompt 84.70% Reasoning On Base model: Nemotron (NVIDIA-Nemotron-Nano-12B-v2) 2026-05-31 Link
IFEval Instruction 89.81% Reasoning On Base model: Nemotron (NVIDIA-Nemotron-Nano-12B-v2) 2026-05-31 Link

Sources

Source links
Pricing data LiteLLM model cost map
Synced at 2026-05-28

Docs

Official docs

Similar models

This list is ranked by overall similarity. Use filters to emphasize the lens that matters most for the replacement you are making.

Comparing from
Model Cost Input shape Features Context Why it is close
Llama-3.3-Nemotron-Super-49B-v1
nebius
In $0.1000 / 1M tokens
Out $0.4000 / 1M tokens
Output: unknown
Function calling
131.1K
Current model
Reference row

Overall blends cost, modality overlap, capabilities, and context.

Model Cost Input shape Features Context Why it is close
Llama-3.3-70B-Instruct
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In $0.1300 / 1M tokens
Out $0.4000 / 1M tokens
Output: unknown
Function calling
128.0K
Same provider
Overall 58%
Meta-Llama-3.1-70B-Instruct
nebius
In $0.1300 / 1M tokens
Out $0.4000 / 1M tokens
Output: unknown
Function calling
128.0K
Same provider
Overall 58%
Qwen2.5-72B-Instruct
nebius
In $0.1300 / 1M tokens
Out $0.4000 / 1M tokens
Output: unknown
Function calling
128.0K
Same provider
Overall 58%
xai.grok-3-mini
oci
In $0.3000 / 1M tokens
Out $0.5000 / 1M tokens
Output: unknown
Function calling
131.1K
Partial I/O overlap
Overall 52%
Qwen2.5-32B-Instruct
nebius
In $0.0600 / 1M tokens
Out $0.2000 / 1M tokens
Output: unknown
Function calling
128.0K
Same provider
Overall 51%
DeepSeek-R1-Distill-Llama-70B
nebius
In $0.2500 / 1M tokens
Out $0.7500 / 1M tokens
Output: unknown
Function calling
128.0K
Same provider
Overall 49%
Llama-3.3-Nemotron-Super-49B-v1.5
deepinfra
In $0.1000 / 1M tokens
Out $0.4000 / 1M tokens
text
Output: text
Function calling
131.1K
Partial I/O overlap
Overall 48%
Mistral-Nemo-Instruct-2407
nebius
In $0.0400 / 1M tokens
Out $0.1200 / 1M tokens
Output: unknown
Function calling
128.0K
Same provider
Overall 47%
Qwen3-32B
nebius
In $0.1000 / 1M tokens
Out $0.3000 / 1M tokens
Output: unknown
Function calling
32.8K
Same provider
Overall 46%
Qwen3-30B-A3B
nebius
In $0.1000 / 1M tokens
Out $0.3000 / 1M tokens
Output: unknown
Function calling
32.8K
Same provider
Overall 46%
Phi-4-mini-reasoning
azure_ai
In $0.0800 / 1M tokens
Out $0.3200 / 1M tokens
text
Output: text
Function calling
4.1K
Partial I/O overlap
Overall 41%
Mixtral-8x22B-Instruct-v0.1
anyscale
In $0.9000 / 1M tokens
Out $0.9000 / 1M tokens
Output: unknown
Function calling
65.5K
Partial I/O overlap
Overall 38%
Mistral-7B-Instruct-v0.1
anyscale
In $0.1500 / 1M tokens
Out $0.1500 / 1M tokens
Output: unknown
Function calling
16.4K
Partial I/O overlap
Overall 37%
Mixtral-8x7B-Instruct-v0.1
anyscale
In $0.1500 / 1M tokens
Out $0.1500 / 1M tokens
Output: unknown
Function calling
16.4K
Partial I/O overlap
Overall 37%
gemini-2.0-flash-001
deepinfra
In $0.1000 / 1M tokens
Out $0.4000 / 1M tokens
audiocode
Output: text
Function calling
1.0M
Partial I/O overlap
Overall 34%
gemini-2.5-flash-lite
vertex_ai-language-models
In $0.1000 / 1M tokens
Out $0.4000 / 1M tokens
audioimage
Output: text
Function calling
65.5K
Partial I/O overlap
Overall 30%
mistral-large-2402
Azure
In $8.0000 / 1M tokens
Out $24.0000 / 1M tokens
Output: unknown
Function calling
32.0K
Partial I/O overlap
Overall 29%
mistral-large-latest
Azure
In $8.0000 / 1M tokens
Out $24.0000 / 1M tokens
Output: unknown
Function calling
32.0K
Partial I/O overlap
Overall 29%
gpt-4.1-nano
Azure
In $0.1000 / 1M tokens
Out $0.4000 / 1M tokens
imagetext
Output: text
Function calling
32.8K
Partial I/O overlap
Overall 27%
gpt-4.1-nano-2025-04-14
Azure
In $0.1000 / 1M tokens
Out $0.4000 / 1M tokens
imagetext
Output: text
Function calling
32.8K
Partial I/O overlap
Overall 27%
command-r-plus
Azure
In $3.0000 / 1M tokens
Out $15.0000 / 1M tokens
text
Output: text
Function calling
4.1K
Partial I/O overlap
Overall 26%
gemini-2.0-flash
vertex_ai-language-models
In $0.1000 / 1M tokens
Out $0.4000 / 1M tokens
audioimage
Output: text
Function calling
8.2K
Partial I/O overlap
Overall 23%