Standard Compute
Model comparison 2026

DeepSeek V4 Flash vs Muse Spark Open

DeepSeek V4 Flash
DeepSeek · Budget · Open weights
$0.12/1M · 1.0M ctx
Muse Spark Open
Meta · Balanced · Open weights
$2.15/1M · 1.0M ctx

Community vote

Pick a winner in each dimension. You can change your vote any time.

Output Quality

Correctness and depth of what it produces

Agentic Ability

Tool calls, instruction-following, and multi-step tasks

Speed

Tokens per second and time-to-first-token

Value for Money

How much capability you get per dollar

Reliability

Consistent results: fewer refusals, loops and format breaks

Specs and pricing side by side

Spec
DeepSeek V4 Flash
Muse Spark Open
Maker
DeepSeek
Meta
Blended price / 1M
$0.12
$2.15
Input / output
$0.09 in · $0.18 out / 1M tokens
$1.25 in · $4.25 out / 1M tokens
Context window
1.0M
1.0M
Open weights
Yes
Yes
Tool use
Yes
Yes
Reasoning
Yes
Yes
Output Quality
7.7
7.0
Agentic Ability
7.1
5.0
Speed
9.1
7.0
Value for Money
9.4
5.3
Reliability
8.7
8.0

Pricing and capabilities synced from the OpenRouter catalogue. Scores are editorial (0–10).

Verdict: DeepSeek V4 Flash or Muse Spark Open?

Updated 2026-10-16

Choose DeepSeek V4 Flash if you want existing setups that still call the deepseek-v4-flash name. Choose Muse Spark Open if you want trying Meta's open-weight coding model through OpenRouter, or self-hosting it where code must stay on your own hardware.

In our editorial scoring, DeepSeek V4 Flash leads in 5 of five dimensions (output quality, agentic ability, speed, value for money and reliability), while Muse Spark Open leads in 0. On price, DeepSeek V4 Flash runs about $0.12 per 1M tokens (blended) and is open-weight; Muse Spark Open is about $2.15 and open-weight.

Where DeepSeek V4 Flash falls short
  • Retired as a DeepSeek API name; calls run V4.1 Flash instead
  • Third-party hosts of the original weights vary in price and speed
Full DeepSeek V4 Flash breakdown →
Where Muse Spark Open falls short
  • No independent agent benchmark results yet; the published figures are Meta's own
  • Self-hosting needs at least 700 GB of GPU memory in NVFP4 (2 TB in BF16), per Meta's model card
Full Muse Spark Open breakdown →

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