Pick GPT-4.1 Mini for very cheap high-volume text work at $0.40 in / $1.60 out per million tokens or instruction following above its weight class — 84.1% on ifeval, beating gpt-4o. 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-4.1 Mini is the value pick.
GPT-4.1 Mini (OpenAI) and Muse Spark 1.3 (Meta) are two of the models people most often weigh against each other in 2026. GPT-4.1 Mini is a cheap, fast 1M-context workhorse with strong instruction following but weak coding — already retired from ChatGPT. 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
Price: GPT-4.1 Mini is about 3.1× cheaper on input ($0.4/$1.6 per 1M tokens vs $1.25/$4.25 per 1M tokens) — meaningful once you are processing millions of tokens a month.
Context window: 1M vs 1M tokens — within a few percent of each other, so treat this as a tie and test on your own long inputs, since usable recall varies by model.
Recency: Muse Spark 1.3 is the newer model by about 17 months (released September 2, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
GPT-4.1 Mini
Muse Spark 1.3
Provider
OpenAI (US)
Meta (US)
Released
April 14, 2025
September 2, 2026
Context window
1M (~1,571 pages)
1M tokens (~1,500 pages)
Price (in/out)
$0.4/$1.6 per 1M tokens
$1.25/$4.25 per 1M tokens
Open weight?
No — API only
No — API only
Modalities
text, image, code
text, image, video
SWE-Bench Verified
23.6%
Not published
MRCR v2 @ 1M
Not published
98.1%
Who wins what
Very cheap high-volume text work at $0.40 in / $1.60 out per million tokens: GPT-4.1 Mini — At $0.4/$1.6 per 1M tokens it undercuts Muse Spark 1.3 ($1.25/$4.25 per 1M tokens), and that gap compounds at volume.
Instruction following above its weight class — 84.1% on IFEval, beating GPT-4o: GPT-4.1 Mini — Muse Spark 1.3 is comparatively weak here — not yet open-weight, despite Meta roadmapping a future Muse Spark weights release
Multi-turn coherence for its tier — 35.8% on MultiChallenge, roughly 1.8x GPT-4o mini: GPT-4.1 Mini — A cheap, fast 1M-context workhorse with strong instruction following but weak coding — already retired from ChatGPT — and it runs cheaper at $0.4/$1.6 per 1M tokens.
Agentic coding with ~20% fewer tool calls and ~25% fewer tokens than Muse Spark 1.2: Muse Spark 1.3 — GPT-4.1 Mini is comparatively weak here — weak at agentic coding — its 23.6% on SWE-Bench Verified sits below GPT-4o's 33.2%
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 is the newer of the two.
Near-perfect long-context retrieval (MRCR v2 512K-1M: 98.1): Muse Spark 1.3 — Muse Spark 1.3 lists near-perfect long-context retrieval (MRCR v2 512K-1M: 98.1) among its strengths; GPT-4.1 Mini does not.
Lowest cost at scale: GPT-4.1 Mini — At $0.4/$1.6 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Which should you pick?
A cost-sensitive startup shipping high volume: GPT-4.1 Mini — At $0.4/$1.6 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: GPT-4.1 Mini — Larger 1M window fits more in one prompt.
Anyone whose priority is very cheap high-volume text work at $0.40 in / $1.60 out per million tokens: GPT-4.1 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-4.1 Mini: where it fits
A cheap, fast 1M-context workhorse with strong instruction following but weak coding — already retired from ChatGPT. Released April 14, 2025 by OpenAI, it is built for very cheap high-volume text work at $0.40 in / $1.60 out per million tokens, instruction following above its weight class — 84.1% on IFEval, beating GPT-4o, multi-turn coherence for its tier — 35.8% on MultiChallenge, roughly 1.8x GPT-4o mini, and a full 1M context at flat pricing, with no long-context premium.
Its trade-offs are real: weak at agentic coding — its 23.6% on SWE-Bench Verified sits below GPT-4o's 33.2%, retired from ChatGPT in February 2026, and OpenAI's own docs now point users to GPT-5 mini instead, and a June 2024 knowledge cutoff, now roughly two years stale, and no reasoning mode. At $0.4 in / $1.6 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-4.1 Mini and Muse Spark 1.3 overlap enough that the right pick depends on your specific job. GPT-4.1 Mini costs less per token; GPT-4.1 Mini holds the larger context; and each leads in its own area — GPT-4.1 Mini for very cheap high-volume text work at $0.40 in / $1.60 out per million tokens, 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.
Frequently asked questions
Is GPT-4.1 Mini or Muse Spark 1.3 better for coding?
Public SWE-Bench figures are not available for Muse Spark 1.3, so the honest test is your own repository — run an identical real bug through both. By design, GPT-4.1 Mini leans toward very cheap high-volume text work at $0.40 in / $1.60 out per million tokens 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-4.1 Mini or Muse Spark 1.3?
GPT-4.1 Mini is cheaper — $0.4/$1.6 per 1M tokens vs $1.25/$4.25 per 1M tokens, roughly 3.1× apart on input.
Which has the bigger context window?
Effectively neither — 1M vs 1M tokens is a difference of a few percent. Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both GPT-4.1 Mini and Muse Spark 1.3 together?
Yes — a multi-model platform like LumiChats gives you GPT-4.1 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-4.1 Mini or Muse Spark 1.3?
Muse Spark 1.3 — released September 2, 2026, about 17 months after GPT-4.1 Mini.
GPT-4.1 Mini vs Muse Spark 1.3
OpenAI · US | Meta · US · Updated June 2026
Quick verdict
Pick GPT-4.1 Mini for very cheap high-volume text work at $0.40 in / $1.60 out per million tokens or instruction following above its weight class — 84.1% on ifeval, beating gpt-4o. 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-4.1 Mini is the value pick.
GPT-4.1 Mini (OpenAI) and Muse Spark 1.3 (Meta) are two of the models people most often weigh against each other in 2026. GPT-4.1 Mini is a cheap, fast 1M-context workhorse with strong instruction following but weak coding — already retired from ChatGPT. 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-4.1 Mini is about 3.1× cheaper on input ($0.4/$1.6 per 1M tokens vs $1.25/$4.25 per 1M tokens) — meaningful once you are processing millions of tokens a month.
▸Context window: 1M vs 1M tokens — within a few percent of each other, so treat this as a tie and test on your own long inputs, since usable recall varies by model.
▸Recency: Muse Spark 1.3 is the newer model by about 17 months (released September 2, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
GPT-4.1 Mini
Muse Spark 1.3
Provider
OpenAI (US)
Meta (US)
Released
April 14, 2025
September 2, 2026
Context window
1M (~1,571 pages)
1M tokens (~1,500 pages)
Price (in/out)
$0.4/$1.6 per 1M tokens
$1.25/$4.25 per 1M tokens
Open weight?
No — API only
No — API only
Modalities
text, image, code
text, image, video
SWE-Bench Verified
23.6%
Not published
MRCR v2 @ 1M
Not published
98.1%
Who wins what
Very cheap high-volume text work at $0.40 in / $1.60 out per million tokens
GPT-4.1 Mini
At $0.4/$1.6 per 1M tokens it undercuts Muse Spark 1.3 ($1.25/$4.25 per 1M tokens), and that gap compounds at volume.
Instruction following above its weight class — 84.1% on IFEval, beating GPT-4o
GPT-4.1 Mini
Muse Spark 1.3 is comparatively weak here — not yet open-weight, despite Meta roadmapping a future Muse Spark weights release
Multi-turn coherence for its tier — 35.8% on MultiChallenge, roughly 1.8x GPT-4o mini
GPT-4.1 Mini
A cheap, fast 1M-context workhorse with strong instruction following but weak coding — already retired from ChatGPT — and it runs cheaper at $0.4/$1.6 per 1M tokens.
Agentic coding with ~20% fewer tool calls and ~25% fewer tokens than Muse Spark 1.2
Muse Spark 1.3
GPT-4.1 Mini is comparatively weak here — weak at agentic coding — its 23.6% on SWE-Bench Verified sits below GPT-4o's 33.2%
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 is the newer of the two.
Muse Spark 1.3 lists near-perfect long-context retrieval (MRCR v2 512K-1M: 98.1) among its strengths; GPT-4.1 Mini does not.
Lowest cost at scale
GPT-4.1 Mini
At $0.4/$1.6 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Which should you pick?
A cost-sensitive startup shipping high volume
→ GPT-4.1 Mini
At $0.4/$1.6 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
→ GPT-4.1 Mini
Larger 1M window fits more in one prompt.
Anyone whose priority is very cheap high-volume text work at $0.40 in / $1.60 out per million tokens
→ GPT-4.1 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-4.1 Mini: where it fits
A cheap, fast 1M-context workhorse with strong instruction following but weak coding — already retired from ChatGPT. Released April 14, 2025 by OpenAI, it is built for very cheap high-volume text work at $0.40 in / $1.60 out per million tokens, instruction following above its weight class — 84.1% on IFEval, beating GPT-4o, multi-turn coherence for its tier — 35.8% on MultiChallenge, roughly 1.8x GPT-4o mini, and a full 1M context at flat pricing, with no long-context premium.
Its trade-offs are real: weak at agentic coding — its 23.6% on SWE-Bench Verified sits below GPT-4o's 33.2%, retired from ChatGPT in February 2026, and OpenAI's own docs now point users to GPT-5 mini instead, and a June 2024 knowledge cutoff, now roughly two years stale, and no reasoning mode. At $0.4 in / $1.6 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-4.1 Mini and Muse Spark 1.3 overlap enough that the right pick depends on your specific job. GPT-4.1 Mini costs less per token; GPT-4.1 Mini holds the larger context; and each leads in its own area — GPT-4.1 Mini for very cheap high-volume text work at $0.40 in / $1.60 out per million tokens, 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-4.1 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.
Is GPT-4.1 Mini or Muse Spark 1.3 better for coding?
Public SWE-Bench figures are not available for Muse Spark 1.3, so the honest test is your own repository — run an identical real bug through both. By design, GPT-4.1 Mini leans toward very cheap high-volume text work at $0.40 in / $1.60 out per million tokens 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-4.1 Mini or Muse Spark 1.3?
GPT-4.1 Mini is cheaper — $0.4/$1.6 per 1M tokens vs $1.25/$4.25 per 1M tokens, roughly 3.1× apart on input.
Which has the bigger context window?
Effectively neither — 1M vs 1M tokens is a difference of a few percent. Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both GPT-4.1 Mini and Muse Spark 1.3 together?
Yes — a multi-model platform like LumiChats gives you GPT-4.1 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-4.1 Mini or Muse Spark 1.3?
Muse Spark 1.3 — released September 2, 2026, about 17 months after GPT-4.1 Mini.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.