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DeepSeek V4.1 Flash vs NVIDIA Nemotron 3 Super 120B A12B

DeepSeek V4.1 Flash grades higher overall (83.5 against 50.3). NVIDIA Nemotron 3 Super 120B A12B costs 45% less for the same work.

DeepSeek V4.1 Flash

by DeepSeek · #11 of 67 overall

Coming soon · price at launch
Context
1M
Input / 1M
$0.20
Output / 1M
$0.60

NVIDIA Nemotron 3 Super 120B A12B

by NVIDIA · #48 of 67 overall

Coming soon · price at launch
Context
256K
Input / 1M
$0.085
Output / 1M
$0.40

Better overall

DeepSeek V4.1 Flash

Grade 83.5 vs 50.3

Cheaper

NVIDIA Nemotron 3 Super 120B A12B

45% less, $0.16 vs $0.30 blended

Larger context

DeepSeek V4.1 Flash

1M vs 256K tokens

Terminal-Bench 2.1

DeepSeek V4.1 Flash

90.6% vs 39.6%

Head to head

Public benchmarks. Longer is better; each value links to its source.

LMArena TextElo-style rating · LMArena (CC BY 4.0) · Oct 15, 2026
DeepSeek V4.1 FlashDeepSeek V4.1 Flash: 1,475
NVIDIA Nemotron 3 Super 120B A12BNVIDIA Nemotron 3 Super 120B A12B: 1,360
LMArena WebDevElo-style rating · LMArena (CC BY 4.0) · Oct 13, 2026
DeepSeek V4.1 FlashDeepSeek V4.1 Flash: 1,619
NVIDIA Nemotron 3 Super 120B A12BNVIDIA Nemotron 3 Super 120B A12B: —
LMArena CodingElo-style rating · LMArena (CC BY 4.0) · Oct 15, 2026
DeepSeek V4.1 FlashDeepSeek V4.1 Flash: 1,523
NVIDIA Nemotron 3 Super 120B A12BNVIDIA Nemotron 3 Super 120B A12B: 1,407
SWE-bench Verified% of issues resolved · SWE-bench · Mar 11, 2026 · reference
DeepSeek V4.1 FlashDeepSeek V4.1 Flash: —
NVIDIA Nemotron 3 Super 120B A12BNVIDIA Nemotron 3 Super 120B A12B: 60.5%v
Terminal-Bench 4.0% of tasks passed · Terminal-Bench · Sep 10, 2026 · reference
DeepSeek V4.1 FlashDeepSeek V4.1 Flash: 31.2%v
NVIDIA Nemotron 3 Super 120B A12BNVIDIA Nemotron 3 Super 120B A12B: —
Terminal-Bench 3.0% of tasks passed · Terminal-Bench · Sep 10, 2026 · reference
DeepSeek V4.1 FlashDeepSeek V4.1 Flash: 30%v
NVIDIA Nemotron 3 Super 120B A12BNVIDIA Nemotron 3 Super 120B A12B: —
Terminal-Bench 2.1% of tasks passed · Terminal-Bench · Sep 10, 2026 · reference
DeepSeek V4.1 FlashDeepSeek V4.1 Flash: 90.6%v
NVIDIA Nemotron 3 Super 120B A12BNVIDIA Nemotron 3 Super 120B A12B: 39.6%v
Terminal-Bench 2.0% of tasks passed · Terminal-Bench · Mar 11, 2026 · reference
DeepSeek V4.1 FlashDeepSeek V4.1 Flash: —
NVIDIA Nemotron 3 Super 120B A12BNVIDIA Nemotron 3 Super 120B A12B: 31%v

DeepSeek V4.1 FlashNVIDIA Nemotron 3 Super 120B A12Bv = reported by the model’s maker. — = no public score yet. Arena bars span the range across every model we grade.

Speed through FullsendAI

Measured through FullsendAI, from one location, Oct 15, 2026, n=20 (5 for long runs).

DeepSeek V4.1 FlashNVIDIA Nemotron 3 Super 120B A12B

Time to first tokenmedian, tick at p90 · lower is faster

DeepSeek V4.1 FlashDeepSeek V4.1 Flash: 393 msp90 739
NVIDIA Nemotron 3 Super 120B A12BNVIDIA Nemotron 3 Super 120B A12B: —

Output speed1,500-token replies, tick at p90

DeepSeek V4.1 FlashDeepSeek V4.1 Flash: 162 t/sp90 197
NVIDIA Nemotron 3 Super 120B A12BNVIDIA Nemotron 3 Super 120B A12B: —

First-try success 55/55 for DeepSeek V4.1 Flash and — for NVIDIA Nemotron 3 Super 120B A12B. FullsendAI retries busy responses automatically, so a missed first try costs a moment, not an error.

How we measured

Streamed chat completions with default settings, the two models alternating run by run. Time to first token runs from sending the request to the first streamed token, connection included, over short prompts. Output speed is output tokens a second after the first token, on long replies. One location and one afternoon, so treat small differences as noise.

What it costs you

Drag to match your monthly usage.

DeepSeek V4.1 Flash$64.00 /month
NVIDIA Nemotron 3 Super 120B A12B$33.00 /month

NVIDIA Nemotron 3 Super 120B A12B saves you $31.00 a month at this usage, $372 a year.

Capabilities

CapabilityDeepSeek V4.1 FlashNVIDIA Nemotron 3 Super 120B A12B
Reasoning levels through FullsendAI YesNo
Reads images through FullsendAI YesNo
Open weights Yes—
Tool calling Yes—
JSON output Yes—
Tool calls that worked (measured)10/10—
Valid JSON replies (measured)10/10—

Our coding quick check (ten small Python functions against hidden tests; not a benchmark): 10/10 for DeepSeek V4.1 Flash, — for NVIDIA Nemotron 3 Super 120B A12B.

Maker-published benchmarks

As each maker reports them, with their own harnesses and settings: not graded, and not strictly comparable across makers.

BenchmarkDeepSeek V4.1 FlashNVIDIA Nemotron 3 Super 120B A12B
Terminal-Bench 2.190.6%—
Terminal-Bench 3.030%—
Terminal-Bench 4.031.2%—
DeepSWE v1.174.2%—
NL2Repo-Bench64—
ProgramBench20.3%—
Codeforces3,471 rating—
SEC-Bench Pro62.8%—
CyberGym88.1%—
ExploitGym15.3%—
HumanEval (base model)79.4%—
BigCodeBench (base model)60.6%—
AutomationBench54.8%—
Agent's Last Exam31.8%—

Each score links to where its maker published it.

At a glance

AttributeDeepSeek V4.1 FlashNVIDIA Nemotron 3 Super 120B A12B
Made byDeepSeekNVIDIA
AvailabilityComing soonComing soon
Overall gradeExcellent · 83.5Good · 50.3
Overall rank#11 of 67#48 of 67
Input price$0.20 per 1M$0.085 per 1M
Output price$0.60 per 1M$0.40 per 1M
Context window1,048,576 tokens262,144 tokens
Reasoning levelsYesNo
Reads imagesYesNo
Model IDdeepseek-v4.1-flashnvidia-nemotron-3-super-120b-a12b
Model card: what the makers publish
FactDeepSeek V4.1 FlashNVIDIA Nemotron 3 Super 120B A12B
ReleasedSep 10, 2026—
Made byDeepSeek (DeepSeek-AI)—
LicenceMIT License (repository and model weights)—
Commercial useAllowed (MIT License permits use, modification, distribution, sublicensing and sale)—
Open weightsYes—
Parameters552B backbone parameters (includes 196B Engram conditional-memory parameters per the card's architecture notes)—
Active parameters8B per token during prefill / 16B per token during decode—
Mixture of expertsYes: 1 shared + 384 routed experts per MoE layer, 6 routed experts active per token—
ArchitectureCausal Encoder-Decoder (CED): 40-layer Transformer = 20-layer causal encoder + 20-layer decoder; decoder global KV projected from final encoder states. Compressed Sparse Attention 2 (CSA2, Full/Reindex/Reuse layer modes, Hierarchical Sparse Indexer), FP4 main KV cache (E2M1, one E4M3 scale per 16 channels), ~890 bytes/token global KV cache (~1/4 of DeepSeek-V4-Flash), SWA Bounded Replay, Single-Pass mHC, Engram conditional memory (196B params), DSpark speculative decoding, DeepSeek-ViT vision encoder + 2-layer MLP projector.—
Context window1,048,576 tokens—
Max output384K (DeepSeek's own API, 'MAXIMUM: 384K')—
InputText, Image—
OutputText—
ReasoningThinking mode with continuously controllable reasoning effort (integer 1-100). DeepSeek API: thinking on by default (effort 'high'); toggle via {"thinking": {"type": "enabled"|"disabled"}}, effort via reasoning_effort low/high/max. In thinking mode temperature/penalties are ignored; reasoning returned in reasoning_content.—
Tool callingYes—
JSON outputJSON Output via response_format {'type':'json_object'} (prompt must mention 'json')—
Recommended samplingtemperature 1.0, top_p 0.95 or 1.0, context_window 1M, max_tokens >= 256K—
Training dataPre-trained from scratch on a 45T-token multimodal corpus; context extended to 1M at 34T tokens—
Other featuresChat Prefix Completion (Beta), FIM Completion (Beta, non-thinking mode only), Responses API and Anthropic-format API on DeepSeek's own endpoint; context caching (cache-hit pricing); vision—
Sources

Try both with one key

Same endpoint, same key, both hosted in the USA. Change one word to switch models, in Claude Code, Cursor, Cline or your own code.

Get your API key
# Ask either model the same thing
curl https://fullsendai.com/v1/chat/completions \
  -H "Authorization: Bearer $FULLSEND_API_KEY" \
  -d '{"model": "deepseek-v4.1-flash", "messages": [...]}'

# …then swap one word
  -d '{"model": "nvidia-nemotron-3-super-120b-a12b", "messages": [...]}'

Questions

Is DeepSeek V4.1 Flash or NVIDIA Nemotron 3 Super 120B A12B better?

DeepSeek V4.1 Flash grades 83.5 against 50.3 for NVIDIA Nemotron 3 Super 120B A12B, from public benchmarks.

Which is cheaper, DeepSeek V4.1 Flash or NVIDIA Nemotron 3 Super 120B A12B?

NVIDIA Nemotron 3 Super 120B A12B: $0.085 in and $0.40 out per million tokens, against $0.20 and $0.60 through FullsendAI.

Which has the larger context window?

DeepSeek V4.1 Flash, with 1,048,576 tokens.

Can I use both with one API key?

Yes, once they launch: both are coming soon, at the prices shown, and both will use the same FullsendAI key.

Compare with others

Model rankingsAll benchmarksCompare other models

Scores: LMArena (CC BY 4.0), SWE-bench, Terminal-Bench, and model makers’ published results where marked v. Prices are FullsendAI’s, per million tokens. Data as of Oct 28, 2026.