GPT-4o mini vs Muse Spark 1.3
OpenAI · US | Meta · US · Updated June 2026
Quick verdict
Pick GPT-4o mini for very low cost per token for its capability tier or strong coding for a small model (87.2% humaneval). Pick Muse Spark 1.3 for agentic coding with ~20% fewer tool calls and ~25% fewer tokens than muse spark 1.2 or deepswe v1.1 long-horizon software engineering (75.4). On a tight budget at scale, GPT-4o mini is the value pick.
GPT-4o mini (OpenAI) and Muse Spark 1.3 (Meta) are two of the models people most often weigh against each other in 2026. GPT-4o mini is openAI's budget small multimodal model — cheap, fast text-and-vision intelligence that outscored peer small models like Gemini 1.5 Flash and Claude 3 Haiku on MMLU and HumanEval at launch. Muse Spark 1.3 is meta's September 2, 2026 agentic-coding model update, cutting tool calls and token usage versus Muse Spark 1.2 while its highest-reasoning mode remains gated for safety review. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences at a glance
- ▸Price: GPT-4o mini is about 8.3× cheaper on input ($0.15/$0.6 per 1M tokens vs $1.25/$4.25 per 1M tokens) — a large enough gap that at scale it can be the single biggest line item in the decision.
- ▸Context window: Muse Spark 1.3 holds 7.8× more — 1M tokens (~1,500 pages) vs 128K (~192 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
- ▸Recency: Muse Spark 1.3 is the newer model by about 26 months (released September 2, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
| Spec | GPT-4o mini | Muse Spark 1.3 |
|---|---|---|
| Provider | OpenAI (US) | Meta (US) |
| Released | July 18, 2024 | September 2, 2026 |
| Context window | 128K (~192 pages) | 1M tokens (~1,500 pages) |
| Price (in/out) | $0.15/$0.6 per 1M tokens | $1.25/$4.25 per 1M tokens |
| Open weight? | No — API only | No — API only |
| Modalities | text, image | text, image, video |
| SWE-Bench Verified | Not published | Not published |
| MRCR v2 @ 1M | Not published | 98.1% |
Who wins what
Very low cost per token for its capability tier
GPT-4o mini
At $0.15/$0.6 per 1M tokens it undercuts Muse Spark 1.3 ($1.25/$4.25 per 1M tokens), and that gap compounds at volume.
Strong coding for a small model (87.2% HumanEval)
GPT-4o mini
Muse Spark 1.3 is comparatively weak here — strongest 'max' reasoning configuration still gated pending additional safety testing
Leading MMLU among peer small models (82%)
GPT-4o mini
OpenAI's budget small multimodal model — cheap, fast text-and-vision intelligence that outscored peer small models like Gemini 1.5 Flash and Claude 3 Haiku on MMLU and HumanEval at launch — and it runs cheaper at $0.15/$0.6 per 1M tokens.
Agentic coding with ~20% fewer tool calls and ~25% fewer tokens than Muse Spark 1.2
Muse Spark 1.3
Its 1M tokens window holds about 7.8× more than GPT-4o mini's 128K in a single prompt.
DeepSWE v1.1 long-horizon software engineering (75.4)
Muse Spark 1.3
Meta's September 2, 2026 agentic-coding model update, cutting tool calls and token usage versus Muse Spark 1.2 while its highest-reasoning mode remains gated for safety review — and it carries the larger 1M tokens context.
Near-perfect long-context retrieval (MRCR v2 512K-1M: 98.1)
Muse Spark 1.3
GPT-4o mini is comparatively weak here — only 128K context with an October 2023 knowledge cutoff
Lowest cost at scale
GPT-4o mini
At $0.15/$0.6 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input
Muse Spark 1.3
Its 1M tokens window is about 7.8× larger than GPT-4o mini's 128K, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ GPT-4o mini
At $0.15/$0.6 per 1M tokens it undercuts Muse Spark 1.3, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Muse Spark 1.3
Larger 1M tokens window fits more in one prompt.
Anyone whose priority is very low cost per token for its capability tier
→ GPT-4o mini
It is specifically built for that.
Anyone whose priority is agentic coding with ~20% fewer tool calls and ~25% fewer tokens than muse spark 1.2
→ Muse Spark 1.3
That is its strongest area.
GPT-4o mini: where it fits
OpenAI's budget small multimodal model — cheap, fast text-and-vision intelligence that outscored peer small models like Gemini 1.5 Flash and Claude 3 Haiku on MMLU and HumanEval at launch. Released July 18, 2024 by OpenAI, it is built for very low cost per token for its capability tier, strong coding for a small model (87.2% HumanEval), leading MMLU among peer small models (82%), and text and image (vision) understanding in the API.
Its trade-offs are real: only 128K context with an October 2023 knowledge cutoff, and weaker on hard reasoning and coding than frontier models. At $0.15 in / $0.6 out per million tokens, it sits in the budget price band.
Muse Spark 1.3: where it fits
Meta's September 2, 2026 agentic-coding model update, cutting tool calls and token usage versus Muse Spark 1.2 while its highest-reasoning mode remains gated for safety review. Released September 2, 2026 by Meta, it is built for agentic coding with ~20% fewer tool calls and ~25% fewer tokens than Muse Spark 1.2, deepSWE v1.1 long-horizon software engineering (75.4), near-perfect long-context retrieval (MRCR v2 512K-1M: 98.1), and ranks third overall on the Artificial Analysis Intelligence Index (score 61, xhigh variant; the limited-preview max variant scores 62) - behind only Claude Fable 5.1 and Claude Opus 5.
Its trade-offs: strongest 'max' reasoning configuration still gated pending additional safety testing, not yet open-weight, despite Meta roadmapping a future Muse Spark weights release, and no official SWE-bench Verified score published. At $1.25 in / $4.25 out per million tokens, it sits in the mid price band.
The bottom line for this matchup
GPT-4o mini and Muse Spark 1.3 overlap enough that the right pick depends on your specific job. GPT-4o mini costs less per token; Muse Spark 1.3 holds the larger context; and each leads in its own area — GPT-4o mini for very low cost per token for its capability tier, Muse Spark 1.3 for agentic coding with ~20% fewer tool calls and ~25% fewer tokens than muse spark 1.2. Rather than crowning one, run the same hard task through both once and let the results decide.
Want both GPT-4o mini and Muse Spark 1.3 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 pricingFrequently asked questions
Is GPT-4o mini or Muse Spark 1.3 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, GPT-4o mini leans toward very low cost per token for its capability tier while Muse Spark 1.3 leans toward agentic coding with ~20% fewer tool calls and ~25% fewer tokens than muse spark 1.2, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, GPT-4o mini or Muse Spark 1.3?
GPT-4o mini is cheaper — $0.15/$0.6 per 1M tokens vs $1.25/$4.25 per 1M tokens, roughly 8.3× apart on input.
Which has the bigger context window?
Muse Spark 1.3 — 1M tokens vs 128K, about 7.8× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both GPT-4o mini and Muse Spark 1.3 together?
Yes — a multi-model platform like LumiChats gives you GPT-4o mini, Muse Spark 1.3 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, GPT-4o mini or Muse Spark 1.3?
Muse Spark 1.3 — released September 2, 2026, about 26 months after GPT-4o mini.
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.