MiniMax M3 vs Muse Spark 1.1
MiniMax M3 wins on Overall, Coding; Muse Spark 1.1 wins on Multimodal. Every numeric field is compared below, with a worked monthly-cost example and a pick rule for each use case.
Verdict at a glance
Choose MiniMax M3 if you…
- Strong agent ability
- Open source
- Low price
- Best for: AI agents, Open source, Chinese
Choose Muse Spark 1.1 if you…
- Completely free open weights
- By Meta
- Self-hostable
- Multimodal
- Best for: Open research, Local deployment, Experimental
Head-to-head aggregate scores
Scores are 0–100, aggregated from public benchmark information and independently weighted across three leaderboards. Rank is out of 22 tracked models.
Aggregated from public sources and independently weighted; methodology on the Terms page. Scores within 3 points are treated as statistically tied.
Specs & pricing — every field side by side
List API prices in USD per 1M tokens. The highlighted cell is the stronger value/capability on that row.
| Dimension | MiniMax M3 | Muse Spark 1.1 | Verdict |
|---|---|---|---|
| Vendor | MiniMax (CN) | Meta (US) | Different vendors |
| Released | 2026.06 | 2026.08 | Muse Spark 1.1 is newer |
| Overall (rank) | 70 · #13 | 61 · #22 | MiniMax M3 +9 |
| Coding | 68 · #13 | 59 · #21 | MiniMax M3 +9 |
| Multimodal | 70 · #18 | 75 · #15 | Muse Spark 1.1 +5 |
| Context window | 1M | 256K | MiniMax M3 larger |
| Max output | 64K | 64K | Tie |
| Effective-context | 90 | 80 | MiniMax M3 more reliable |
| Input $/1M | $0.6 | Free | Muse Spark 1.1 cheaper |
| Output $/1M | $2.4 | Free | Muse Spark 1.1 cheaper |
| Cache discount | none | none | Tie |
| Speed | ~60 tok/s | Hardware-dependent | MiniMax M3 faster |
| TTFT | 0.5s | Hardware-dependent | MiniMax M3 snappier |
| Function calling | 84 | 65 | MiniMax M3 ahead |
| Refusal rate | ~7% | ~4% | Muse Spark 1.1 less restrictive |
| English | 70 | 78 | Muse Spark 1.1 |
| Chinese | 88 | 60 | MiniMax M3 |
| Modalities | text | text, image | different coverage |
| Open weights | Yes | Yes | Both open |
| Fine-tuning | Yes | Yes | |
| Free tier | Hailuo AI free; open-platform quota | Fully free (model weights) | |
| SOC2 / no-train | no / yes | no / yes | |
| Private deployment | Yes | Yes | Both support it |
Fields drawn from vendor public documentation and the Modelspectra 22-model dataset; speed varies with network, concurrency and prompt length. Verify current pricing before purchase.
Dimension-by-dimension analysis
Reasoning & overall intelligence
MiniMax M3 leads the overall aggregate by 9 points (70 vs 61). That is a meaningful, not marginal, edge on hard, multi-step reasoning, while Muse Spark 1.1 remains a strong generalist that is not out of its depth on routine work.
Agentic coding
This is a modest gap: MiniMax M3 scores 68 against 59. On multi-file edits, SWE-style tickets and long-horizon agent loops MiniMax M3 needs fewer correction turns; Muse Spark 1.1 is still competent for scripts and assisted completion but trails as task complexity rises.
Multimodal
Muse Spark 1.1 leads multimodal 75 vs 70. A concrete modality difference: Muse Spark 1.1 additionally handles image. Neither emits native video, so the comparison is about parsing images and documents, not generation.
Speed & latency
Muse Spark 1.1 is self-hosted, so its speed depends on your hardware; against a managed API like MiniMax M3 (~60 tok/s, 0.5s TTFT) compare on your own infrastructure before assuming latency.
Context: window vs usable recall
Nominal windows are 1M for MiniMax M3 and 256K for Muse Spark 1.1. Effective-context scores point the same way as window size — MiniMax M3 is ahead on usable recall (90 vs 80), so prefer it for long-document work where details cannot be missed.
Price & total cost
Muse Spark 1.1 is free open weights (you pay only for the infrastructure you run it on), while MiniMax M3 is a paid API at $0.6/$2.4 per 1M tokens. The real comparison is total cost of ownership — GPU/ops against a managed bill — not list price alone.
Chinese vs English
English: MiniMax M3 70 vs Muse Spark 1.1 78. Chinese: 88 vs 60. For Chinese-language production, MiniMax M3 is the stronger pick. Note that non-Chinese models generally require overseas network access for their APIs.
Tool use & ecosystem
Function-calling score: MiniMax M3 84 vs Muse Spark 1.1 65, so MiniMax M3 has the edge on structured tool use. Fine-tuning is available from MiniMax M3 and Muse Spark 1.1. Factor in existing SDK/plugin familiarity — switching cost often outweighs a few-point tool-use gap.
Cost worked example — same workload, real token math
Assume a production workload of 100M input + 30M output tokens per month, with 90% of input tokens served from cache. Figures use public list prices.
Illustrative model; your input/output mix and cache-hit ratio change the result. Prices are list rates before any enterprise agreement.