Pick Muse Spark 1.3 for agentic coding with ~20% fewer tool calls and ~25% fewer tokens than muse spark 1.2 or deepswe v1.1 long-horizon software engineering (75.4). Pick NVIDIA Nemotron 3 Super for high-throughput agentic reasoning (up to 2.2x gpt-oss-120b) or 1m-token context with strong long-context retrieval (91.6% ruler @ 1m). Choose NVIDIA Nemotron 3 Super if you need self-hosting or data privacy; Muse Spark 1.3 if you want a managed API.
Muse Spark 1.3 (Meta) and NVIDIA Nemotron 3 Super (NVIDIA) are two of the models people most often weigh against each other in 2026. Muse Spark 1.3 is meta's September 2, 2026 agentic-coding model update, cutting tool calls and token usage versus Muse Spark 1.2 while its highest-reasoning mode remains gated for safety review. NVIDIA Nemotron 3 Super is nVIDIA's open 120B-total/12B-active hybrid Mamba-Transformer MoE built for high-throughput agentic reasoning at 1M-token context. They diverge most on price and open vs. closed weights — each quantified below from the models' real specs.
Key differences
Cost model: NVIDIA Nemotron 3 Super ships open weights you can self-host (hardware cost only, no per-token fee), while Muse Spark 1.3 is API-metered at $1.25/$4.25 per 1M tokens. Your choice depends on whether you want zero marginal cost at the price of running infrastructure.
Context window: both advertise 1M tokens (~1,500 pages). Tie on paper — test on your own long inputs, since usable recall varies by model.
Recency: Muse Spark 1.3 is the newer model by about 6 months (released September 2, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
Muse Spark 1.3
NVIDIA Nemotron 3 Super
Provider
Meta (US)
NVIDIA (US)
Released
September 2, 2026
March 11, 2026
Context window
1M tokens (~1,500 pages)
1M (~1,500 pages)
Price (in/out)
$1.25/$4.25 per 1M tokens
Open weight (self-host / free)
Open weight?
No — API only
Yes — self-hostable
Modalities
text, image, video
text, code
SWE-Bench Verified
Not published
60.47%
MRCR v2 @ 1M
98.1%
Not published
Who wins what
Agentic coding with ~20% fewer tool calls and ~25% fewer tokens than Muse Spark 1.2: Muse Spark 1.3 — Meta's September 2, 2026 agentic-coding model update, cutting tool calls and token usage versus Muse Spark 1.2 while its highest-reasoning mode remains gated for safety review — and it is the newer of the two.
DeepSWE v1.1 long-horizon software engineering (75.4): Muse Spark 1.3 — Muse Spark 1.3 lists deepSWE v1.1 long-horizon software engineering (75.4) among its strengths; NVIDIA Nemotron 3 Super does not.
Near-perfect long-context retrieval (MRCR v2 512K-1M: 98.1): Muse Spark 1.3 — Muse Spark 1.3 lists near-perfect long-context retrieval (MRCR v2 512K-1M: 98.1) among its strengths; NVIDIA Nemotron 3 Super does not.
High-throughput agentic reasoning (up to 2.2x GPT-OSS-120B): NVIDIA Nemotron 3 Super — Muse Spark 1.3 is comparatively weak here — strongest 'max' reasoning configuration still gated pending additional safety testing
1M-token context with strong long-context retrieval (91.6% RULER @ 1M): NVIDIA Nemotron 3 Super — NVIDIA's open 120B-total/12B-active hybrid Mamba-Transformer MoE built for high-throughput agentic reasoning at 1M-token context — and its weights are open while Muse Spark 1.3 is API-only.
Strong math reasoning (90.21% AIME 2025): NVIDIA Nemotron 3 Super — NVIDIA Nemotron 3 Super lists strong math reasoning (90.21% AIME 2025) among its strengths; Muse Spark 1.3 does not.
Lowest cost at scale: NVIDIA Nemotron 3 Super — Its weights are open, so at volume you pay for your own hardware instead of Muse Spark 1.3's $1.25/$4.25 per 1M tokens.
Which should you pick?
A cost-sensitive startup shipping high volume: NVIDIA Nemotron 3 Super — At Open weight (self-host / free) it undercuts Muse Spark 1.3, and on millions of tokens that margin decides the monthly bill.
A team with data-privacy or self-hosting needs: NVIDIA Nemotron 3 Super — Open weights let you run it on your own hardware; Muse Spark 1.3 is API-only.
Anyone whose priority is agentic coding with ~20% fewer tool calls and ~25% fewer tokens than muse spark 1.2: Muse Spark 1.3 — It is specifically built for that.
Anyone whose priority is high-throughput agentic reasoning (up to 2.2x gpt-oss-120b): NVIDIA Nemotron 3 Super — That is its strongest area.
Muse Spark 1.3: where it fits
Meta's September 2, 2026 agentic-coding model update, cutting tool calls and token usage versus Muse Spark 1.2 while its highest-reasoning mode remains gated for safety review. Released September 2, 2026 by Meta, it is built for agentic coding with ~20% fewer tool calls and ~25% fewer tokens than Muse Spark 1.2, deepSWE v1.1 long-horizon software engineering (75.4), near-perfect long-context retrieval (MRCR v2 512K-1M: 98.1), and ranks third overall on the Artificial Analysis Intelligence Index (score 61, xhigh variant; the limited-preview max variant scores 62) - behind only Claude Fable 5.1 and Claude Opus 5.
Its trade-offs are real: strongest 'max' reasoning configuration still gated pending additional safety testing, not yet open-weight, despite Meta roadmapping a future Muse Spark weights release, and no official SWE-bench Verified score published. At $1.25 in / $4.25 out per million tokens, it sits in the mid price band.
NVIDIA Nemotron 3 Super: where it fits
NVIDIA's open 120B-total/12B-active hybrid Mamba-Transformer MoE built for high-throughput agentic reasoning at 1M-token context. Released March 11, 2026 by NVIDIA, it is built for high-throughput agentic reasoning (up to 2.2x GPT-OSS-120B), 1M-token context with strong long-context retrieval (91.6% RULER @ 1M), strong math reasoning (90.21% AIME 2025), and fully open weights, datasets, and recipes for self-hosting.
Its trade-offs: text-only; no image, audio, or video input, and requires roughly 8x H100-80GB GPUs to self-host at BF16. As an open-weight model, its running cost is your own hardware rather than a per-token fee.
The bottom line for this matchup
The defining split here is open vs. closed. NVIDIA Nemotron 3 Super gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. Muse Spark 1.3 gives you a managed, always-updated API with no infrastructure to run. Teams with GPUs, privacy requirements, or huge volume often favour the open model; teams that want zero ops and the latest capabilities favour the closed one. Capability is close enough that this operational question, not the benchmark, usually decides it.
Frequently asked questions
Is Muse Spark 1.3 or NVIDIA Nemotron 3 Super better for coding?
Public SWE-Bench figures are not available for Muse Spark 1.3, so the honest test is your own repository — run an identical real bug through both. By design, Muse Spark 1.3 leans toward agentic coding with ~20% fewer tool calls and ~25% fewer tokens than muse spark 1.2 while NVIDIA Nemotron 3 Super leans toward high-throughput agentic reasoning (up to 2.2x gpt-oss-120b), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Muse Spark 1.3 or NVIDIA Nemotron 3 Super?
NVIDIA Nemotron 3 Super is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Muse Spark 1.3 is API-metered at $1.25/$4.25 per 1M tokens. For most teams without GPUs, the API model is cheaper to start; at very high volume, self-hosting can win.
Which has the bigger context window?
Both advertise 1M tokens (~1,500 pages). Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both Muse Spark 1.3 and NVIDIA Nemotron 3 Super together?
Yes — a multi-model platform like LumiChats gives you Muse Spark 1.3, NVIDIA Nemotron 3 Super and 40+ others under one ₹69/day pass (about $1/day), so you can draft with one and cross-check with the other instead of buying two subscriptions.
Which is newer, Muse Spark 1.3 or NVIDIA Nemotron 3 Super?
Muse Spark 1.3 — released September 2, 2026, about 6 months after NVIDIA Nemotron 3 Super.
Muse Spark 1.3 vs NVIDIA Nemotron 3 Super
Meta · US | NVIDIA · US · Updated June 2026
Quick verdict
Pick Muse Spark 1.3 for agentic coding with ~20% fewer tool calls and ~25% fewer tokens than muse spark 1.2 or deepswe v1.1 long-horizon software engineering (75.4). Pick NVIDIA Nemotron 3 Super for high-throughput agentic reasoning (up to 2.2x gpt-oss-120b) or 1m-token context with strong long-context retrieval (91.6% ruler @ 1m). Choose NVIDIA Nemotron 3 Super if you need self-hosting or data privacy; Muse Spark 1.3 if you want a managed API.
Muse Spark 1.3 (Meta) and NVIDIA Nemotron 3 Super (NVIDIA) are two of the models people most often weigh against each other in 2026. Muse Spark 1.3 is meta's September 2, 2026 agentic-coding model update, cutting tool calls and token usage versus Muse Spark 1.2 while its highest-reasoning mode remains gated for safety review. NVIDIA Nemotron 3 Super is nVIDIA's open 120B-total/12B-active hybrid Mamba-Transformer MoE built for high-throughput agentic reasoning at 1M-token context. They diverge most on price and open vs. closed weights — each quantified below from the models' real specs.
Key differences at a glance
▸Cost model: NVIDIA Nemotron 3 Super ships open weights you can self-host (hardware cost only, no per-token fee), while Muse Spark 1.3 is API-metered at $1.25/$4.25 per 1M tokens. Your choice depends on whether you want zero marginal cost at the price of running infrastructure.
▸Context window: both advertise 1M tokens (~1,500 pages). Tie on paper — test on your own long inputs, since usable recall varies by model.
▸Recency: Muse Spark 1.3 is the newer model by about 6 months (released September 2, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
Muse Spark 1.3
NVIDIA Nemotron 3 Super
Provider
Meta (US)
NVIDIA (US)
Released
September 2, 2026
March 11, 2026
Context window
1M tokens (~1,500 pages)
1M (~1,500 pages)
Price (in/out)
$1.25/$4.25 per 1M tokens
Open weight (self-host / free)
Open weight?
No — API only
Yes — self-hostable
Modalities
text, image, video
text, code
SWE-Bench Verified
Not published
60.47%
MRCR v2 @ 1M
98.1%
Not published
Who wins what
Agentic coding with ~20% fewer tool calls and ~25% fewer tokens than Muse Spark 1.2
Muse Spark 1.3
Meta's September 2, 2026 agentic-coding model update, cutting tool calls and token usage versus Muse Spark 1.2 while its highest-reasoning mode remains gated for safety review — and it is the newer of the two.
Muse Spark 1.3 lists near-perfect long-context retrieval (MRCR v2 512K-1M: 98.1) among its strengths; NVIDIA Nemotron 3 Super does not.
High-throughput agentic reasoning (up to 2.2x GPT-OSS-120B)
NVIDIA Nemotron 3 Super
Muse Spark 1.3 is comparatively weak here — strongest 'max' reasoning configuration still gated pending additional safety testing
1M-token context with strong long-context retrieval (91.6% RULER @ 1M)
NVIDIA Nemotron 3 Super
NVIDIA's open 120B-total/12B-active hybrid Mamba-Transformer MoE built for high-throughput agentic reasoning at 1M-token context — and its weights are open while Muse Spark 1.3 is API-only.
Strong math reasoning (90.21% AIME 2025)
NVIDIA Nemotron 3 Super
NVIDIA Nemotron 3 Super lists strong math reasoning (90.21% AIME 2025) among its strengths; Muse Spark 1.3 does not.
Lowest cost at scale
NVIDIA Nemotron 3 Super
Its weights are open, so at volume you pay for your own hardware instead of Muse Spark 1.3's $1.25/$4.25 per 1M tokens.
Which should you pick?
A cost-sensitive startup shipping high volume
→ NVIDIA Nemotron 3 Super
At Open weight (self-host / free) it undercuts Muse Spark 1.3, and on millions of tokens that margin decides the monthly bill.
A team with data-privacy or self-hosting needs
→ NVIDIA Nemotron 3 Super
Open weights let you run it on your own hardware; Muse Spark 1.3 is API-only.
Anyone whose priority is agentic coding with ~20% fewer tool calls and ~25% fewer tokens than muse spark 1.2
→ Muse Spark 1.3
It is specifically built for that.
Anyone whose priority is high-throughput agentic reasoning (up to 2.2x gpt-oss-120b)
→ NVIDIA Nemotron 3 Super
That is its strongest area.
Muse Spark 1.3: where it fits
Meta's September 2, 2026 agentic-coding model update, cutting tool calls and token usage versus Muse Spark 1.2 while its highest-reasoning mode remains gated for safety review. Released September 2, 2026 by Meta, it is built for agentic coding with ~20% fewer tool calls and ~25% fewer tokens than Muse Spark 1.2, deepSWE v1.1 long-horizon software engineering (75.4), near-perfect long-context retrieval (MRCR v2 512K-1M: 98.1), and ranks third overall on the Artificial Analysis Intelligence Index (score 61, xhigh variant; the limited-preview max variant scores 62) - behind only Claude Fable 5.1 and Claude Opus 5.
Its trade-offs are real: strongest 'max' reasoning configuration still gated pending additional safety testing, not yet open-weight, despite Meta roadmapping a future Muse Spark weights release, and no official SWE-bench Verified score published. At $1.25 in / $4.25 out per million tokens, it sits in the mid price band.
NVIDIA Nemotron 3 Super: where it fits
NVIDIA's open 120B-total/12B-active hybrid Mamba-Transformer MoE built for high-throughput agentic reasoning at 1M-token context. Released March 11, 2026 by NVIDIA, it is built for high-throughput agentic reasoning (up to 2.2x GPT-OSS-120B), 1M-token context with strong long-context retrieval (91.6% RULER @ 1M), strong math reasoning (90.21% AIME 2025), and fully open weights, datasets, and recipes for self-hosting.
Its trade-offs: text-only; no image, audio, or video input, and requires roughly 8x H100-80GB GPUs to self-host at BF16. As an open-weight model, its running cost is your own hardware rather than a per-token fee.
The bottom line for this matchup
The defining split here is open vs. closed. NVIDIA Nemotron 3 Super gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. Muse Spark 1.3 gives you a managed, always-updated API with no infrastructure to run. Teams with GPUs, privacy requirements, or huge volume often favour the open model; teams that want zero ops and the latest capabilities favour the closed one. Capability is close enough that this operational question, not the benchmark, usually decides it.
Want both Muse Spark 1.3 and NVIDIA Nemotron 3 Super without two subscriptions? LumiChats gives you these plus 40+ models under one ₹69/day pass (about $1/day) — draft with one, cross-check with the other.
Is Muse Spark 1.3 or NVIDIA Nemotron 3 Super better for coding?
Public SWE-Bench figures are not available for Muse Spark 1.3, so the honest test is your own repository — run an identical real bug through both. By design, Muse Spark 1.3 leans toward agentic coding with ~20% fewer tool calls and ~25% fewer tokens than muse spark 1.2 while NVIDIA Nemotron 3 Super leans toward high-throughput agentic reasoning (up to 2.2x gpt-oss-120b), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Muse Spark 1.3 or NVIDIA Nemotron 3 Super?
NVIDIA Nemotron 3 Super is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Muse Spark 1.3 is API-metered at $1.25/$4.25 per 1M tokens. For most teams without GPUs, the API model is cheaper to start; at very high volume, self-hosting can win.
Which has the bigger context window?
Both advertise 1M tokens (~1,500 pages). Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both Muse Spark 1.3 and NVIDIA Nemotron 3 Super together?
Yes — a multi-model platform like LumiChats gives you Muse Spark 1.3, NVIDIA Nemotron 3 Super and 40+ others under one ₹69/day pass (about $1/day), so you can draft with one and cross-check with the other instead of buying two subscriptions.
Which is newer, Muse Spark 1.3 or NVIDIA Nemotron 3 Super?
Muse Spark 1.3 — released September 2, 2026, about 6 months after NVIDIA Nemotron 3 Super.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.