Neither wins outright: DeepSeek: DeepSeek V4.1 Flash 1017 is the pick when you need seed (reproducible sampling), Meta: Muse Spark 1.3 Contributor when cost matters at scale.
| Spec | DeepSeek: DeepSeek V4.1 Flash 1017 | Meta: Muse Spark 1.3 Contributor |
|---|---|---|
| Provider | DeepSeek | Meta |
| Input price (per 1M tokens) | $0.15 | $0.10 |
| Output price (per 1M tokens) | $0.60 | $0.20 |
| Blended price (3:1 input/output) | $0.26 | $0.13 |
| Cheaper than … of all models we track | 64% | 77% |
| Context window | 1.0M tokens (~1,573 pages) | 1.0M tokens (~1,573 pages) |
| Larger context than … of all models | 80% | 80% |
| Max output per response | 393K tokens (~294,900 words) | 944K tokens (~707,800 words) |
| Input types | text, image | text, image, video, file |
| Output types | text | text |
| Free variant | No | No |
| Listed since | 2026-10-17 | 2026-09-02 |
Monthly cost at list price for five common workloads. Token counts per unit are stated so you can scale them to your own traffic. A workload that does not fit a model's context window is marked rather than priced.
| Workload (per month) | DeepSeek: DeepSeek V4.1 Flash 1017 | Meta: Muse Spark 1.3 Contributor | Difference |
|---|---|---|---|
| Customer-support chatbot 50,000 conversations — each a 6-turn conversation (1,500 in / 400 out tokens) | $23.25 | $11.50 | Meta: Muse Spark 1.3 Contributor saves $11.75 |
| RAG search over documents 20,000 questions — each a question answered from ~8 retrieved passages (6,000 in / 500 out tokens) | $24.00 | $14.00 | Meta: Muse Spark 1.3 Contributor saves $10.00 |
| Coding / tool-using agent 2,000 tasks — each a multi-step task with tool calls and file context (60,000 in / 6,000 out tokens) | $25.20 | $14.40 | Meta: Muse Spark 1.3 Contributor saves $10.80 |
| Batch summarisation 10,000 documents — each a 6,000-word report summarised to a page (8,000 in / 600 out tokens) | $15.60 | $9.20 | Meta: Muse Spark 1.3 Contributor saves $6.40 |
| Long-document analysis 500 documents — each a 150-page contract or codebase read in one pass (100,000 in / 2,000 out tokens) | $8.10 | $5.20 | Meta: Muse Spark 1.3 Contributor saves $2.90 |
| Capability | DeepSeek: DeepSeek V4.1 Flash 1017 | Meta: Muse Spark 1.3 Contributor | What it lets you do |
|---|---|---|---|
| Tool / function calling | ✓ Yes | ✓ Yes | call your APIs and run agent loops |
| Structured output (JSON schema) | ✓ Yes | ✓ Yes | return JSON that validates against your schema |
| Reasoning / thinking mode | ✓ Yes | ✓ Yes | spend extra tokens thinking before answering hard problems |
| Image input | ✓ Yes | ✓ Yes | read screenshots, charts and scanned pages |
| Audio input | — | — | take speech or audio directly |
| File / PDF input | — | ✓ Yes | accept documents without your own parsing step |
| Image output | — | — | generate images, not just text |
| Built-in web search | — | ✓ Yes | answer from live web results |
| Seed (reproducible sampling) | ✓ Yes | — | repeat a generation for tests and evals |
| Log-probabilities | ✓ Yes | — | read token confidence for classification and scoring |
From each model's published parameters and input/output types. “—” means not advertised, not proven absent.
Neither wins outright: DeepSeek: DeepSeek V4.1 Flash 1017 is the pick when you need seed (reproducible sampling), Meta: Muse Spark 1.3 Contributor when cost matters at scale. In short: DeepSeek: DeepSeek V4.1 Flash 1017 when you need seed (reproducible sampling), you need log-probabilities; Meta: Muse Spark 1.3 Contributor when cost matters at scale, you need file / PDF input, you need built-in web search, you generate long outputs in one go.
Meta: Muse Spark 1.3 Contributor is cheaper: $0.13 vs $0.26 per 1M tokens at a typical 3:1 input/output mix, 52% less. For 50,000 support conversations a month that is $11.50 against $23.25.
DeepSeek: DeepSeek V4.1 Flash 1017 costs $0.15 per 1M input tokens and $0.60 per 1M output tokens; Meta: Muse Spark 1.3 Contributor costs $0.10 input and $0.20 output. Output tokens are billed separately, so long answers shift the gap.
Both take 1.0M tokens per request — roughly 1,573 pages of text.
Tool calling — DeepSeek: DeepSeek V4.1 Flash 1017: yes, Meta: Muse Spark 1.3 Contributor: yes. JSON-schema structured output — DeepSeek: DeepSeek V4.1 Flash 1017: yes, Meta: Muse Spark 1.3 Contributor: yes.
Yes, both accept image input.
No free variant is listed for either; both are pay-per-token.
DeepSeek: DeepSeek V4.1 Flash 1017 can write up to 393K tokens (about 294,900 words) per response; Meta: Muse Spark 1.3 Contributor up to 944K (about 707,800 words).
DeepSeek: DeepSeek V4.1 Flash 1017 was listed on 2026-10-17; Meta: Muse Spark 1.3 Contributor on 2026-09-02.
DeepSeek V4.1 Flash 1017 is the October 17, 2026 snapshot of DeepSeek V4.1 Flash, served by DeepSeek under the `deepseek-flash` API model name. V4.1 Flash is a sparse mixture-of-experts model...
Full DeepSeek: DeepSeek V4.1 Flash 1017 specs →Muse Spark 1.3 Contributor is the cost-efficient contributor tier of Meta’s multimodal reasoning model for experimentation, learning, and early-stage agentic, multi-agent, and coding workflows. It is designed to track information...
Full Meta: Muse Spark 1.3 Contributor specs →