Muse Wonder 1.0 vs Step 3.7 Flash

Meta · US  |  StepFun · China · Updated June 2026

Quick verdict

Pick Muse Wonder 1.0 for meta superintelligence labs' first frontier-class reasoning model — a new line distinct from the agentic-coding-focused muse spark family or artificial analysis intelligence index score of 52 (a gated 'wonder full' subscription variant scores 56, tied with claude sonnet 5.5, behind only opus 5.5 at 58). Pick Step 3.7 Flash for a 198b-parameter sparse moe vision-language model (11b active) built specifically for agentic coding and search workflows or scmp reported it 'outshines larger rivals' from deepseek and moonshot on some benchmarks despite its smaller active size. Choose Step 3.7 Flash if you need self-hosting or data privacy; Muse Wonder 1.0 if you want a managed API.

Muse Wonder 1.0 (Meta, US) and Step 3.7 Flash (StepFun, China) line up two different AI ecosystems against each other — a comparison that is as much about cost philosophy and openness as raw capability. Muse Wonder 1.0 is meta Superintelligence Labs' October 12, 2026 debut frontier model — distinct from Muse Spark, scoring 52 on the independent Artificial Analysis Index with a 1M-token, four-modality context window. Step 3.7 Flash is stepFun's 198B MoE vision-language model built for coding and search agents - a distinct Chinese lab with genuinely competitive open weights. They diverge most on price, context window and open vs. closed weights — each quantified below from the models' real specs.

Key differences at a glance

Side-by-side specs

SpecMuse Wonder 1.0Step 3.7 Flash
ProviderMeta (US) StepFun (China)
ReleasedOctober 12, 2026 May 29, 2026
Context window1M tokens (~1,573 pages) 256K (~393 pages)
Price (in/out)$4/$20 per 1M tokens $0.2/$1.15 per 1M tokens
Open weight?No — API only Yes — self-hostable
Modalitiestext, image, video, audio text, image, code
SWE-Bench VerifiedNot published Not published
MRCR v2 @ 1MNot published Not published

Who wins what

Meta Superintelligence Labs' first frontier-class reasoning model — a new line distinct from the agentic-coding-focused Muse Spark family

Muse Wonder 1.0

Meta Superintelligence Labs' October 12, 2026 debut frontier model — distinct from Muse Spark, scoring 52 on the independent Artificial Analysis Index with a 1M-token, four-modality context window — and it carries the larger 1M tokens context.

Artificial Analysis Intelligence Index score of 52 (a gated 'Wonder Full' subscription variant scores 56, tied with Claude Sonnet 5.5, behind only Opus 5.5 at 58)

Muse Wonder 1.0

Meta Superintelligence Labs' October 12, 2026 debut frontier model — distinct from Muse Spark, scoring 52 on the independent Artificial Analysis Index with a 1M-token, four-modality context window — and it is the newer of the two.

78.8% on DeepSWE v1.1 long-horizon coding, ahead of both Claude Opus 5.5 (74.2%) and GPT-6 Astra (74.1%)

Muse Wonder 1.0

Its 1M tokens window holds about 4× more than Step 3.7 Flash's 256K in a single prompt.

A 198B-parameter sparse MoE vision-language model (11B active) built specifically for agentic coding and search workflows

Step 3.7 Flash

Muse Wonder 1.0 is comparatively weak here — first release in a brand-new model family — no track record yet next to Meta's more established Muse Spark line

SCMP reported it 'outshines larger rivals' from DeepSeek and Moonshot on some benchmarks despite its smaller active size

Step 3.7 Flash

Muse Wonder 1.0 is comparatively weak here — benchmark comparisons against Opus 5.5 and GPT-6 Astra are Meta's own self-reported figures

Open weights (Apache 2.0) at a low per-token price

Step 3.7 Flash

At $0.2/$1.15 per 1M tokens it undercuts Muse Wonder 1.0 ($4/$20 per 1M tokens), and that gap compounds at volume.

Lowest cost at scale

Step 3.7 Flash

At $0.2/$1.15 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.

Largest single-prompt input

Muse Wonder 1.0

Its 1M tokens window is about 4× larger than Step 3.7 Flash's 256K, fitting roughly 1,573 pages in one prompt.

Which should you pick?

A cost-sensitive startup shipping high volume

→ Step 3.7 Flash

At $0.2/$1.15 per 1M tokens it undercuts Muse Wonder 1.0, and on millions of tokens that margin decides the monthly bill.

Someone analysing very long documents or codebases

→ Muse Wonder 1.0

Larger 1M tokens window fits more in one prompt.

A team with data-privacy or self-hosting needs

→ Step 3.7 Flash

Open weights let you run it on your own hardware; Muse Wonder 1.0 is API-only.

Anyone whose priority is meta superintelligence labs' first frontier-class reasoning model — a new line distinct from the agentic-coding-focused muse spark family

→ Muse Wonder 1.0

It is specifically built for that.

Anyone whose priority is a 198b-parameter sparse moe vision-language model (11b active) built specifically for agentic coding and search workflows

→ Step 3.7 Flash

That is its strongest area.

An enterprise with regional data-residency rules

→ Muse Wonder 1.0 or Step 3.7 Flash

Origin (US vs China) affects where data is processed and which compliance regime applies — check the provider's terms for your region.

Muse Wonder 1.0: where it fits

Meta Superintelligence Labs' October 12, 2026 debut frontier model — distinct from Muse Spark, scoring 52 on the independent Artificial Analysis Index with a 1M-token, four-modality context window. Released October 12, 2026 by Meta, it is built for meta Superintelligence Labs' first frontier-class reasoning model — a new line distinct from the agentic-coding-focused Muse Spark family, artificial Analysis Intelligence Index score of 52 (a gated 'Wonder Full' subscription variant scores 56, tied with Claude Sonnet 5.5, behind only Opus 5.5 at 58), 78.8% on DeepSWE v1.1 long-horizon coding, ahead of both Claude Opus 5.5 (74.2%) and GPT-6 Astra (74.1%), and accepts text, image, video, audio, and PDF input against a 1,048,576-token context window.

Its trade-offs are real: the stronger 'Wonder Full' variant is gated behind $50/$200-per-month Muse Code subscriptions, with no public API or independently verifiable pricing, meta's full safety report had not been published as of launch, first release in a brand-new model family — no track record yet next to Meta's more established Muse Spark line, and benchmark comparisons against Opus 5.5 and GPT-6 Astra are Meta's own self-reported figures. At $4 in / $20 out per million tokens, it sits in the mid price band.

Step 3.7 Flash: where it fits

StepFun's 198B MoE vision-language model built for coding and search agents - a distinct Chinese lab with genuinely competitive open weights. Released May 29, 2026 by StepFun, it is built for a 198B-parameter sparse MoE vision-language model (11B active) built specifically for agentic coding and search workflows, sCMP reported it 'outshines larger rivals' from DeepSeek and Moonshot on some benchmarks despite its smaller active size, open weights (Apache 2.0) at a low per-token price, and includes a 1.8B vision encoder for image understanding alongside text.

Its trade-offs: stepFun is a newer, less established lab than DeepSeek, Alibaba, or Moonshot, benchmark 'outshines rivals' claims are from press coverage of specific tests, not a full independent leaderboard sweep, and smaller ecosystem and less third-party documentation than the more established Chinese labs. At $0.2 in / $1.15 out per million tokens, it sits in the budget price band.

The bottom line for this matchup

The defining split here is open vs. closed. Step 3.7 Flash gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. Muse Wonder 1.0 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 Wonder 1.0 and Step 3.7 Flash 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.

See pricing

Frequently asked questions

Is Muse Wonder 1.0 or Step 3.7 Flash better for coding?

Public SWE-Bench figures are not available for either model, so the honest test is your own repository — run an identical real bug through both. By design, Muse Wonder 1.0 leans toward meta superintelligence labs' first frontier-class reasoning model — a new line distinct from the agentic-coding-focused muse spark family while Step 3.7 Flash leans toward a 198b-parameter sparse moe vision-language model (11b active) built specifically for agentic coding and search workflows, and that positioning usually predicts which feels better on your codebase.

Which is cheaper, Muse Wonder 1.0 or Step 3.7 Flash?

Step 3.7 Flash is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Muse Wonder 1.0 is API-metered at $4/$20 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?

Muse Wonder 1.0 — 1M tokens vs 256K, about 4× larger. Useful only if the model actually reasons over the full window, which not all do.

Can I use both Muse Wonder 1.0 and Step 3.7 Flash together?

Yes — a multi-model platform like LumiChats gives you Muse Wonder 1.0, Step 3.7 Flash 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 Wonder 1.0 or Step 3.7 Flash?

Muse Wonder 1.0 — released October 12, 2026, about 5 months after Step 3.7 Flash.

Related comparisons

Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.