DeepSeek V4-Flash vs Muse Spark Open

DeepSeek · China  |  Meta · US · Updated June 2026

Quick verdict

Pick DeepSeek V4-Flash for exceptional value — artificial analysis intelligence index 52 at just $0.14/$0.28 per million tokens or mit-licensed open weights — free to self-host or run via a western host. Pick Muse Spark Open for meta's first open-weight muse model - 816b-parameter moe with 42b active, accepting text, image, video and audio input or artificial analysis intelligence index of 39, first among us open-weight models. On a tight budget at scale, Muse Spark Open is the value pick.

DeepSeek V4-Flash (DeepSeek, China) and Muse Spark Open (Meta, US) line up two different AI ecosystems against each other — a comparison that is as much about cost philosophy and openness as raw capability. DeepSeek V4-Flash is deepSeek's MIT-licensed open-weight model — arguably the best value-per-intelligence available, scoring 52 on the independent AA Index at just $0.14/$0.28 per million tokens. Muse Spark Open is meta's October 15, 2026 open-weight Muse Spark - an 816B/42B-active multimodal MoE with a 1M context under a gated Muse Model License. Their biggest split is price, and the breakdown below shows exactly how that plays out for your workload.

Key differences at a glance

Side-by-side specs

SpecDeepSeek V4-FlashMuse Spark Open
ProviderDeepSeek (China) Meta (US)
ReleasedJuly 31, 2026 October 15, 2026
Context window1M (~1,500 pages) 1M tokens (~1,500 pages)
Price (in/out)$0.22/$0.66 per 1M tokens Open weight (self-host / free)
Open weight?Yes — self-hostable Yes — self-hostable
Modalitiestext, code text, image, video, audio, code
SWE-Bench VerifiedNot published Not published
MRCR v2 @ 1MNot published Not published

Who wins what

Exceptional value — Artificial Analysis Intelligence Index 52 at just $0.14/$0.28 per million tokens

DeepSeek V4-Flash

DeepSeek V4-Flash lists exceptional value — Artificial Analysis Intelligence Index 52 at just $0.14/$0.28 per million tokens among its strengths; Muse Spark Open does not.

MIT-licensed open weights — free to self-host or run via a Western host

DeepSeek V4-Flash

DeepSeek V4-Flash lists mIT-licensed open weights — free to self-host or run via a Western host among its strengths; Muse Spark Open does not.

1M-token context window

DeepSeek V4-Flash

Muse Spark Open is comparatively weak here — needs about 1 TB of memory at 4-bit; no first-party per-token price confirmed

Meta's first open-weight Muse model - 816B-parameter MoE with 42B active, accepting text, image, video and audio input

Muse Spark Open

DeepSeek V4-Flash is comparatively weak here — text and code focused — not a full multimodal model

Artificial Analysis Intelligence Index of 39, first among US open-weight models

Muse Spark Open

DeepSeek V4-Flash is comparatively weak here — below the top frontier models on overall intelligence

About 143 output tokens/sec; up to 128K output tokens

Muse Spark Open

Meta's October 15, 2026 open-weight Muse Spark - an 816B/42B-active multimodal MoE with a 1M context under a gated Muse Model License — and it is the newer of the two.

Lowest cost at scale

Muse Spark Open

Its weights are open, so at volume you pay for your own hardware instead of DeepSeek V4-Flash's $0.22/$0.66 per 1M tokens.

Which should you pick?

A cost-sensitive startup shipping high volume

→ Muse Spark Open

At Open weight (self-host / free) it undercuts DeepSeek V4-Flash, and on millions of tokens that margin decides the monthly bill.

Anyone whose priority is exceptional value — artificial analysis intelligence index 52 at just $0.14/$0.28 per million tokens

→ DeepSeek V4-Flash

It is specifically built for that.

Anyone whose priority is meta's first open-weight muse model - 816b-parameter moe with 42b active, accepting text, image, video and audio input

→ Muse Spark Open

That is its strongest area.

An enterprise with regional data-residency rules

→ Muse Spark Open or DeepSeek V4-Flash

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

DeepSeek V4-Flash: where it fits

DeepSeek's MIT-licensed open-weight model — arguably the best value-per-intelligence available, scoring 52 on the independent AA Index at just $0.14/$0.28 per million tokens. Released July 31, 2026 by DeepSeek, it is built for exceptional value — Artificial Analysis Intelligence Index 52 at just $0.14/$0.28 per million tokens, mIT-licensed open weights — free to self-host or run via a Western host, 1M-token context window, and strong coding and agentic performance for the price (DeepSeek reports 82.7 on Terminal-Bench 2.1).

Its trade-offs are real: coding/agentic figures like Terminal-Bench 82.7 are DeepSeek's own, not independently reproduced, text and code focused — not a full multimodal model, deepSeek's own hosted API stores data in China; self-host or use a Western host for privacy, and below the top frontier models on overall intelligence. At $0.22 in / $0.66 out per million tokens, it sits in the budget price band.

Muse Spark Open: where it fits

Meta's October 15, 2026 open-weight Muse Spark - an 816B/42B-active multimodal MoE with a 1M context under a gated Muse Model License. Released October 15, 2026 by Meta, it is built for meta's first open-weight Muse model - 816B-parameter MoE with 42B active, accepting text, image, video and audio input, artificial Analysis Intelligence Index of 39, first among US open-weight models, and about 143 output tokens/sec; up to 128K output tokens.

Its trade-offs: weakest of the three Muse models (Wonder Full scores 56, Wonder 52), muse Model License: attribution required and a revenue threshold (reported as about $20M; check the license text) before a separate license is needed, and needs about 1 TB of memory at 4-bit; no first-party per-token price confirmed. As an open-weight model, its running cost is your own hardware rather than a per-token fee.

The bottom line for this matchup

This is less "which is smarter" and more "which ecosystem fits." DeepSeek V4-Flash (China) and Muse Spark Open (US) differ on pricing philosophy, data-residency, and tooling as much as on raw scores. Muse Spark Open is the cheaper option, which matters at volume. The pragmatic move is to run one real task through both and judge the outputs against your own constraints — including where your data is allowed to be processed.

Want both DeepSeek V4-Flash and Muse Spark Open 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 DeepSeek V4-Flash or Muse Spark Open 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, DeepSeek V4-Flash leans toward exceptional value — artificial analysis intelligence index 52 at just $0.14/$0.28 per million tokens while Muse Spark Open leans toward meta's first open-weight muse model - 816b-parameter moe with 42b active, accepting text, image, video and audio input, and that positioning usually predicts which feels better on your codebase.

Which is cheaper, DeepSeek V4-Flash or Muse Spark Open?

Muse Spark Open is cheaper — $0.22/$0.66 per 1M tokens vs Open weight (self-host / free).

Which has the bigger context window?

Both advertise 1M (~1,500 pages). Remember advertised ≠ usable: recall typically degrades before the ceiling.

Can I use both DeepSeek V4-Flash and Muse Spark Open together?

Yes — a multi-model platform like LumiChats gives you DeepSeek V4-Flash, Muse Spark Open 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, DeepSeek V4-Flash or Muse Spark Open?

Muse Spark Open — released October 15, 2026, about 3 months after DeepSeek V4-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.