Meta’s latest AI mannequin Muse Spark 1.3, unveiled yesterday, is quicker and extra performant on third-party benchmarks than its predecessor — with a caveat.
"Muse Spark 1.3 is rolling out at present with frontier efficiency virtually too low-cost to meter," Meta co-founder and CEO Mark Zuckerberg wrote on X, calling IT Meta’s “largest bounce” but in coding and agentic work.
There’s substance behind each components of that declare. Muse Spark 1.3 makes vital beneficial properties over final month’s 1.2 launch, notably on long-running agent duties. The model builders can entry now can also be one of many strongest price-performance choices close to the highest of impartial mannequin rankings.
Meta’s strongest Muse Spark 1.3 benchmark outcomes come from its max reasoning configuration. Meta says that model continues to be finishing extra security testing and can arrive “shortly”; the third-party benchmarking agency Artificial Analysis says IT evaluated max in a restricted companion preview, and presently lists no API supplier in any respect for the configuration.
The model broadly rolling out this week by its Muse Code harness and the Meta Model API makes use of Meta’s beforehand obtainable reasoning settings, together with xhigh.
That makes the extra related enterprise query not whether or not Muse Spark 1.3 can attain frontier territory, however how shut the mannequin firms can truly deploy at present will get — and at what actual value.
The transport mannequin is superb, however not the benchmark chief
Meta does disclose outcomes for each configurations in its underlying analysis report, so this isn’t a case of the corporate hiding the deployable mannequin. However its launch supplies prominently showcase the max variant, and a number of the largest scores belong to that configuration.
For instance, Meta reviews GDPval-AA v2 scores of 1,754 Elo for max versus 1,709 for xhigh, OSWorld 2.0 scores of 66.9 versus 57.2, and JobBench scores of 64.9 versus 61.2.
On some assessments the excellence is negligible or reversed: DeepSearchQA is tied at 89.4, whereas xhigh scores 89.2 on Terminal-Bench 2.1 versus max at 88.8.
Artificial Analysis scores Muse Spark 1.3 max at 62 on its Intelligence Index and the transport xhigh model at 61. The latter ties GPT-5.6 Sol max, Grok 4.6 excessive and Claude Opus 5 excessive. However Anthropic nonetheless occupies the highest of the leaderboard: Claude Fable 5.1 reaches 66 at max and 65 at xhigh, whereas Claude Opus 5 reaches 63 at max and xhigh.
In different phrases, Muse Spark 1.3 xhigh is legitimately within the frontier cluster, however IT will not be the mannequin presently setting the frontier.
That’s nonetheless a considerable change from Muse Spark 1.2. VentureBeat’s protection of final month’s launch discovered Meta fielding a reputable coding challenger that nonetheless usually trailed Anthropic’s finest mannequin. Muse Spark 1.2 scored 82.9% on Terminal-Bench 2.1 versus Opus 5’s 86.7%, and likewise completed behind Opus on the opposite predominant coding comparisons Meta introduced.
With 1.3, Meta is now not merely displaying up in that contest. On a number of coding and agentic evaluations, IT is buying and selling wins with OpenAI and Anthropic.
Meta says the underlying mannequin has additionally grow to be simpler to function. Muse Spark 1.3 is educated to keep up a number of workflows in a protracted thread, collect context with instruments, detect gaps in its personal plans, ask customers for clarification when mandatory and ensure earlier than consequential actions. In Meta engineers’ inside comparisons, IT used roughly 20% fewer device calls and 25% fewer tokens than 1.2 throughout coding work.
For enterprises paying for hundreds or thousands and thousands of agent loops, these behavioral enhancements may matter greater than one other leaderboard level.
‘Virtually too low-cost to meter’ doesn’t imply Meta reduce its costs
Muse Spark 1.3 didn’t obtain an API value reduce. Meta stored Customary pricing precisely the place IT was for Muse Spark 1.2: $1.25 per million enter tokens, $4.25 per million output tokens and $0.15 per million cached enter tokens.
|
Mannequin |
Enter ($/1M) |
Output ($/1M) |
Complete ($/1M) |
Supply |
|
Muse Spark 1.2 / 1.3 Contributor |
$0.10 |
$0.20 |
$0.30 |
|
|
MiMo-V2.5 Flash |
$0.10 |
$0.30 |
$0.40 |
|
|
DeepSeek-V4-Flash — off-peak |
$0.22 |
$0.66 |
$0.88 |
|
|
GPT-5.6 Luna |
$0.20 |
$1.20 |
$1.40 |
|
|
MiniMax-M3 |
$0.30 |
$1.20 |
$1.50 |
|
|
LongCat-2.0 — limited-time promo |
$0.30 |
$1.20 |
$1.50 |
|
|
DeepSeek-V4-Flash — peak hours |
$0.44 |
$1.32 |
$1.76 |
|
|
MiMo-V2.5 |
$0.40 |
$2.00 |
$2.40 |
|
|
DeepSeek-V4-Professional — off-peak |
$0.66 |
$1.98 |
$2.64 |
|
|
LongCat-2.0 — customary |
$0.75 |
$2.95 |
$3.70 |
|
|
MiMo-V2.5 Professional (≤256K) |
$1.00 |
$3.00 |
$4.00 |
|
|
Gemini 3.7 Flash — by Dec. 31, 2026 |
$0.75 |
$3.75 |
$4.50 |
|
|
Gemini 3.8 Flash — by Dec. 31, 2026 |
$0.75 |
$3.75 |
$4.50 |
|
|
DeepSeek-V4-Professional — peak hours |
$1.32 |
$3.96 |
$5.28 |
|
|
Muse Spark 1.1 / 1.2 / 1.3 |
$1.25 |
$4.25 |
$5.50 |
|
|
GLM-5.3 |
$1.40 |
$4.40 |
$5.80 |
|
|
Grok 4.6 — <200K immediate tokens |
$2.00 |
$6.00 |
$8.00 |
|
|
MiMo-V2.5 Professional (>256K) |
$2.00 |
$6.00 |
$8.00 |
|
|
Qwen3.8-Max |
$2.00 |
$6.00 |
$8.00 |
|
|
Gemini 3.7 Flash — beginning Jan. 1, 2027 |
$1.50 |
$7.50 |
$9.00 |
|
|
Gemini 3.8 Flash — beginning Jan. 1, 2027 |
$1.50 |
$7.50 |
$9.00 |
|
|
GPT-5.6 Terra |
$2.00 |
$12.00 |
$14.00 |
|
|
Grok 4.6 — ≥200K immediate tokens |
$4.00 |
$12.00 |
$16.00 |
|
|
GPT-5.4 |
$2.50 |
$15.00 |
$17.50 |
|
|
Kimi K3 |
$3.00 |
$15.00 |
$18.00 |
|
|
Claude Opus 5 |
$5.00 |
$25.00 |
$30.00 |
|
|
Sakana Fugu Extremely (≤272K) |
$5.00 |
$30.00 |
$35.00 |
|
|
GPT-5.6 Sol — Customary mode |
$5.00 |
$30.00 |
$35.00 |
|
|
Claude Fable 5 / Claude Mythos 5 |
$10.00 |
$50.00 |
$60.00 |
|
|
Claude Fable 5.1 / Claude Mythos 5.1 |
$10.00 |
$50.00 |
$60.00 |
|
|
GPT-5.6 Sol — Quick mode |
$10.00 |
$60.00 |
$70.00 |
That makes Zuckerberg’s “virtually too low-cost to meter” line much less a press release about decrease token costs than about what Meta believes builders can accomplish with these tokens.
Artificial Analysis provides proof for that argument, but additionally a complication. IT measures Muse Spark 1.3 xhigh at 235.2 output tokens per second and estimates a price of $0.55 per Intelligence Index process.
At 61 on the Intelligence Index, that offers IT the lowest value per process of any presently measured mannequin at that intelligence stage.
Muse Spark 1.2 value solely $0.40 per Synthetic Evaluation process, whereas scoring 57.
Regardless of unchanged per-token pricing, the impartial benchmark’s value of finishing a mean process due to this fact elevated generation-over-generation. Synthetic Evaluation attributes the rise primarily to heavier input-token consumption on agentic evaluations.
That doesn’t straight contradict Meta’s declare of 25% decrease token use: Meta is describing comparisons in its personal coding workflows, whereas Synthetic Evaluation is measuring a broader suite of reasoning and agentic duties.
However IT illustrates why “low-cost” turns into slippery as soon as fashions function as brokers. Token charges, reasoning effort, variety of turns, device calls and retries all contribute to the precise value of ending work.
Meta additionally retains its unusually low-cost Contributor tier — $0.10 per million enter tokens and $0.20 per million output tokens — in change for permission to make use of prompts and completions for coaching.
As VentureBeat famous with Muse Spark 1.2, that could be engaging for prototyping however creates a materially completely different data-governance calculation for enterprises working with proprietary code or delicate inside Information.
Wang’s ‘Gemini who?’ lands on an unusually shut comparability
Meta chief AI officer Alexandr Wang was significantly much less certified in celebrating the discharge.
After Synthetic Evaluation posted its Muse Spark outcomes, Wang reposted them on X, adding: “i actually hate to say IT, however… gemini who? 😱💨”
The shade was notably pointed as a result of Google launched Gemini 3.8 Flash on the identical day, pitching IT at virtually precisely the identical class of workload: long-horizon software program engineering, autonomous brokers and multi-step skilled reasoning. Google calls 3.8 its finest reasoning and coding Flash mannequin but and says IT is the corporate’s third Flash launch in six weeks.
Unbiased numbers give Wang one thing to work with, although hardly a knockout.
Synthetic Evaluation offers Muse Spark 1.3 xhigh a 61 Intelligence Index rating at $0.55 per process, in contrast with 59 and $0.58 for Gemini 3.8 Flash at excessive reasoning. Meta due to this fact edges Google on each intelligence and process value at these explicit settings.
Google wins decisively on throughput. Synthetic Evaluation measures Gemini 3.8 Flash excessive at about 305 output tokens per second, versus 235 for Muse Spark — roughly 30% sooner. Gemini additionally has the decrease uncooked API sticker value for now: Google is charging an introductory $0.75 per million enter tokens and $3.75 per million output tokens, in contrast with Meta’s $1.25 and $4.25.
That promotional Google pricing expires December 31, after which IT rises to $1.50 per million enter tokens and $7.50 per million output tokens.
The result’s a helpful snapshot of how tight frontier-model economics have grow to be. Meta presently wins this impartial comparability by two Intelligence Index factors and three cents per benchmark process; Google provides considerably greater output throughput and cheaper uncooked tokens throughout its launch promotion.
Wang’s “gemini who?” is enjoyable govt trash speak. For an enterprise architect, the reply is nearer to: Gemini is the sooner possibility; Muse is presently the marginally stronger high-effort agent by this impartial measure.
Meta's evolving open weights stance
The extra consequential difficulty for some builders might have little to do with at present’s benchmark race.
When Meta launched Muse Code and Muse Spark 1.2 in August, VentureBeat famous how dramatically the corporate had moved away from the open-weight technique that made Llama ubiquitous.
Muse Code and Spark 1.2 have been proprietary, API-served merchandise — a placing posture for the corporate that had spent years arguing that open AI was the trail ahead.
5 days later, Meta modified course once more.
On August 10, IT launched the 30-billion-parameter Muse Glimmer underneath an Apache 2.0 license. Zuckerberg additionally mentioned: “Within the coming weeks, we’re additionally going to open the weights for Muse Spark 1.2.” Reuters individually reported Meta’s plan to launch the Spark 1.2 weights.
Now, Meta has as a substitute shipped Muse Spark 1.3 as one other proprietary mannequin.
That doesn’t but quantity to a damaged promise — “coming weeks” can fairly describe a interval longer than three weeks. However at present’s announcement makes the roadmap much less clear reasonably than extra.
Meta’s new publish now not says Muse Spark 1.2. IT says its roadmap contains “the Muse Spark open weights launch”, with out figuring out a model, launch date, mannequin measurement or license. Zuckerberg likewise mentioned on X that “Muse Spark open weights releases” are coming quickly.
For groups that standardized on Llama as a result of downloadable weights meant self-hosting, customization and management over inference economics, that ambiguity might matter greater than whether or not Spark gained one other level on a composite benchmark.
Muse Spark 1.3 exhibits that Meta can now iterate proprietary frontier fashions at extraordinary pace. The transport xhigh configuration is quick, competitively priced and far nearer to the highest of impartial rankings than its predecessors. The max preview exhibits Meta can push the household a bit of additional when allowed to spend extra reasoning compute.
The subsequent check is completely different: whether or not Meta can convert that tempo right into a roadmap enterprises can truly plan round — together with making its finest capabilities broadly deployable and delivering the open-weight Spark mannequin IT has already mentioned is coming.
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