Pick Grok 4.7 for 2.1 trillion parameters, up 40% from grok 4.6's 1.5 trillion, at the same $2/$6 per million token price or deepswe v1.1 (high effort): 71.0%, up from grok 4.6's 65.2%; cursorbench 4.0: 46.3%, up from 40.4%. Pick Mercury 2.5 Preview for very high inference throughput (1,107 tok/s) via diffusion-based parallel token generation or coding accuracy (95.7%, 91st percentile among cost-optimized models). On a tight budget at scale, Mercury 2.5 Preview is the value pick.
Grok 4.7 (xAI) and Mercury 2.5 Preview (Inception Labs) are two of the models people most often weigh against each other in 2026. Grok 4.7 is xAI's September 21, 2026 update — a 2.1T-parameter model trained partly on SpaceX hardware data, same price as Grok 4.6 but stronger on coding benchmarks. Mercury 2.5 Preview is inception Labs' August 31, 2026 diffusion-based language model preview, refining tokens in parallel for roughly 10x the throughput of comparable autoregressive models at cost-optimized-tier quality. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences
Price: Mercury 2.5 Preview is about 50× cheaper on input ($0.04/$0.15 per 1M tokens vs $2/$6 per 1M tokens) — a large enough gap that at scale it can be the single biggest line item in the decision.
Context window: Grok 4.7 holds 1.9× more — 500K tokens (~750 pages) vs 260K tokens (~390 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
Recency: Grok 4.7 is the newer model by about 21 days (released September 21, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
Grok 4.7
Mercury 2.5 Preview
Provider
xAI (US)
Inception Labs (US)
Released
September 21, 2026
August 31, 2026
Context window
500K tokens (~750 pages)
260K tokens (~390 pages)
Price (in/out)
$2/$6 per 1M tokens
$0.04/$0.15 per 1M tokens
Open weight?
No — API only
No — API only
Modalities
text, image, code
text
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
2.1 trillion parameters, up 40% from Grok 4.6's 1.5 trillion, at the same $2/$6 per million token price: Grok 4.7 — Its 500K tokens window holds about 1.9× more than Mercury 2.5 Preview's 260K tokens in a single prompt.
DeepSWE v1.1 (high effort): 71.0%, up from Grok 4.6's 65.2%; CursorBench 4.0: 46.3%, up from 40.4%: Grok 4.7 — XAI's September 21, 2026 update — a 2.1T-parameter model trained partly on SpaceX hardware data, same price as Grok 4.6 but stronger on coding benchmarks — and it carries the larger 500K tokens context.
Trained with supplemental SpaceX data (Starlink telemetry, manufacturing records, engineering failure logs) — xAI says this improves reasoning about hardware and physical systems: Grok 4.7 — XAI's September 21, 2026 update — a 2.1T-parameter model trained partly on SpaceX hardware data, same price as Grok 4.6 but stronger on coding benchmarks — and it is the newer of the two.
Very high inference throughput (1,107 tok/s) via diffusion-based parallel token generation: Mercury 2.5 Preview — Inception Labs' August 31, 2026 diffusion-based language model preview, refining tokens in parallel for roughly 10x the throughput of comparable autoregressive models at cost-optimized-tier quality — and it runs cheaper at $0.04/$0.15 per 1M tokens.
Coding accuracy (95.7%, 91st percentile among cost-optimized models): Mercury 2.5 Preview — At $0.04/$0.15 per 1M tokens it undercuts Grok 4.7 ($2/$6 per 1M tokens), and that gap compounds at volume.
Mathematics accuracy (97.0%, 97th percentile): Mercury 2.5 Preview — Mercury 2.5 Preview lists mathematics accuracy (97.0%, 97th percentile) among its strengths; Grok 4.7 does not.
Lowest cost at scale: Mercury 2.5 Preview — At $0.04/$0.15 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input: Grok 4.7 — Its 500K tokens window is about 1.9× larger than Mercury 2.5 Preview's 260K tokens, fitting roughly 750 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume: Mercury 2.5 Preview — At $0.04/$0.15 per 1M tokens it undercuts Grok 4.7, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: Grok 4.7 — Larger 500K tokens window fits more in one prompt.
Anyone whose priority is 2.1 trillion parameters, up 40% from grok 4.6's 1.5 trillion, at the same $2/$6 per million token price: Grok 4.7 — It is specifically built for that.
Anyone whose priority is very high inference throughput (1,107 tok/s) via diffusion-based parallel token generation: Mercury 2.5 Preview — That is its strongest area.
Grok 4.7: where it fits
XAI's September 21, 2026 update — a 2.1T-parameter model trained partly on SpaceX hardware data, same price as Grok 4.6 but stronger on coding benchmarks. Released September 21, 2026 by xAI, it is built for 2.1 trillion parameters, up 40% from Grok 4.6's 1.5 trillion, at the same $2/$6 per million token price, deepSWE v1.1 (high effort): 71.0%, up from Grok 4.6's 65.2%; CursorBench 4.0: 46.3%, up from 40.4%, trained with supplemental SpaceX data (Starlink telemetry, manufacturing records, engineering failure logs) — xAI says this improves reasoning about hardware and physical systems, and xAI's strongest safety guardrails to date, per the company.
Its trade-offs are real: release was delayed at least five times since late July 2026 before shipping, 500K context window trails several rivals now sitting at 1M+, and reviewers note it arrives "late to the AI frontier party" against GPT-6 Astra, Claude Fable 5.1 and Opus 5.5, all shipped in the weeks just before it. At $2 in / $6 out per million tokens, it sits in the mid price band.
Mercury 2.5 Preview: where it fits
Inception Labs' August 31, 2026 diffusion-based language model preview, refining tokens in parallel for roughly 10x the throughput of comparable autoregressive models at cost-optimized-tier quality. Released August 31, 2026 by Inception Labs, it is built for very high inference throughput (1,107 tok/s) via diffusion-based parallel token generation, coding accuracy (95.7%, 91st percentile among cost-optimized models), mathematics accuracy (97.0%, 97th percentile), and tunable reasoning levels with parallel tool calls and schema-aligned JSON output.
Its trade-offs: 260K context window is far shorter than frontier 1M-token models, no vision or audio modalities, positioned only against cost-optimized models (GPT-5.6 Luna Low, Gemini 3.5 Flash-Lite), not frontier-class, and current $0.04/$0.15 pricing includes a limited-time launch promotion on OpenRouter (list price is $0.20/$0.75, may rise after Sept 8, 2026). At $0.04 in / $0.15 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
Grok 4.7 and Mercury 2.5 Preview overlap enough that the right pick depends on your specific job. Mercury 2.5 Preview costs less per token; Grok 4.7 holds the larger context; and each leads in its own area — Grok 4.7 for 2.1 trillion parameters, up 40% from grok 4.6's 1.5 trillion, at the same $2/$6 per million token price, Mercury 2.5 Preview for very high inference throughput (1,107 tok/s) via diffusion-based parallel token generation. Rather than crowning one, run the same hard task through both once and let the results decide.
Frequently asked questions
Is Grok 4.7 or Mercury 2.5 Preview 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, Grok 4.7 leans toward 2.1 trillion parameters, up 40% from grok 4.6's 1.5 trillion, at the same $2/$6 per million token price while Mercury 2.5 Preview leans toward very high inference throughput (1,107 tok/s) via diffusion-based parallel token generation, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Grok 4.7 or Mercury 2.5 Preview?
Mercury 2.5 Preview is cheaper — $2/$6 per 1M tokens vs $0.04/$0.15 per 1M tokens, roughly 50× apart on input.
Which has the bigger context window?
Grok 4.7 — 500K tokens vs 260K tokens, about 1.9× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Grok 4.7 and Mercury 2.5 Preview together?
Yes — a multi-model platform like LumiChats gives you Grok 4.7, Mercury 2.5 Preview 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, Grok 4.7 or Mercury 2.5 Preview?
Grok 4.7 — released September 21, 2026, about 21 days after Mercury 2.5 Preview.
Grok 4.7 vs Mercury 2.5 Preview
xAI · US | Inception Labs · US · Updated June 2026
Quick verdict
Pick Grok 4.7 for 2.1 trillion parameters, up 40% from grok 4.6's 1.5 trillion, at the same $2/$6 per million token price or deepswe v1.1 (high effort): 71.0%, up from grok 4.6's 65.2%; cursorbench 4.0: 46.3%, up from 40.4%. Pick Mercury 2.5 Preview for very high inference throughput (1,107 tok/s) via diffusion-based parallel token generation or coding accuracy (95.7%, 91st percentile among cost-optimized models). On a tight budget at scale, Mercury 2.5 Preview is the value pick.
Grok 4.7 (xAI) and Mercury 2.5 Preview (Inception Labs) are two of the models people most often weigh against each other in 2026. Grok 4.7 is xAI's September 21, 2026 update — a 2.1T-parameter model trained partly on SpaceX hardware data, same price as Grok 4.6 but stronger on coding benchmarks. Mercury 2.5 Preview is inception Labs' August 31, 2026 diffusion-based language model preview, refining tokens in parallel for roughly 10x the throughput of comparable autoregressive models at cost-optimized-tier quality. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences at a glance
▸Price: Mercury 2.5 Preview is about 50× cheaper on input ($0.04/$0.15 per 1M tokens vs $2/$6 per 1M tokens) — a large enough gap that at scale it can be the single biggest line item in the decision.
▸Context window: Grok 4.7 holds 1.9× more — 500K tokens (~750 pages) vs 260K tokens (~390 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
▸Recency: Grok 4.7 is the newer model by about 21 days (released September 21, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
Grok 4.7
Mercury 2.5 Preview
Provider
xAI (US)
Inception Labs (US)
Released
September 21, 2026
August 31, 2026
Context window
500K tokens (~750 pages)
260K tokens (~390 pages)
Price (in/out)
$2/$6 per 1M tokens
$0.04/$0.15 per 1M tokens
Open weight?
No — API only
No — API only
Modalities
text, image, code
text
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
2.1 trillion parameters, up 40% from Grok 4.6's 1.5 trillion, at the same $2/$6 per million token price
Grok 4.7
Its 500K tokens window holds about 1.9× more than Mercury 2.5 Preview's 260K tokens in a single prompt.
DeepSWE v1.1 (high effort): 71.0%, up from Grok 4.6's 65.2%; CursorBench 4.0: 46.3%, up from 40.4%
Grok 4.7
XAI's September 21, 2026 update — a 2.1T-parameter model trained partly on SpaceX hardware data, same price as Grok 4.6 but stronger on coding benchmarks — and it carries the larger 500K tokens context.
Trained with supplemental SpaceX data (Starlink telemetry, manufacturing records, engineering failure logs) — xAI says this improves reasoning about hardware and physical systems
Grok 4.7
XAI's September 21, 2026 update — a 2.1T-parameter model trained partly on SpaceX hardware data, same price as Grok 4.6 but stronger on coding benchmarks — and it is the newer of the two.
Very high inference throughput (1,107 tok/s) via diffusion-based parallel token generation
Mercury 2.5 Preview
Inception Labs' August 31, 2026 diffusion-based language model preview, refining tokens in parallel for roughly 10x the throughput of comparable autoregressive models at cost-optimized-tier quality — and it runs cheaper at $0.04/$0.15 per 1M tokens.
Coding accuracy (95.7%, 91st percentile among cost-optimized models)
Mercury 2.5 Preview
At $0.04/$0.15 per 1M tokens it undercuts Grok 4.7 ($2/$6 per 1M tokens), and that gap compounds at volume.
Mathematics accuracy (97.0%, 97th percentile)
Mercury 2.5 Preview
Mercury 2.5 Preview lists mathematics accuracy (97.0%, 97th percentile) among its strengths; Grok 4.7 does not.
Lowest cost at scale
Mercury 2.5 Preview
At $0.04/$0.15 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input
Grok 4.7
Its 500K tokens window is about 1.9× larger than Mercury 2.5 Preview's 260K tokens, fitting roughly 750 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Mercury 2.5 Preview
At $0.04/$0.15 per 1M tokens it undercuts Grok 4.7, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Grok 4.7
Larger 500K tokens window fits more in one prompt.
Anyone whose priority is 2.1 trillion parameters, up 40% from grok 4.6's 1.5 trillion, at the same $2/$6 per million token price
→ Grok 4.7
It is specifically built for that.
Anyone whose priority is very high inference throughput (1,107 tok/s) via diffusion-based parallel token generation
→ Mercury 2.5 Preview
That is its strongest area.
Grok 4.7: where it fits
XAI's September 21, 2026 update — a 2.1T-parameter model trained partly on SpaceX hardware data, same price as Grok 4.6 but stronger on coding benchmarks. Released September 21, 2026 by xAI, it is built for 2.1 trillion parameters, up 40% from Grok 4.6's 1.5 trillion, at the same $2/$6 per million token price, deepSWE v1.1 (high effort): 71.0%, up from Grok 4.6's 65.2%; CursorBench 4.0: 46.3%, up from 40.4%, trained with supplemental SpaceX data (Starlink telemetry, manufacturing records, engineering failure logs) — xAI says this improves reasoning about hardware and physical systems, and xAI's strongest safety guardrails to date, per the company.
Its trade-offs are real: release was delayed at least five times since late July 2026 before shipping, 500K context window trails several rivals now sitting at 1M+, and reviewers note it arrives "late to the AI frontier party" against GPT-6 Astra, Claude Fable 5.1 and Opus 5.5, all shipped in the weeks just before it. At $2 in / $6 out per million tokens, it sits in the mid price band.
Mercury 2.5 Preview: where it fits
Inception Labs' August 31, 2026 diffusion-based language model preview, refining tokens in parallel for roughly 10x the throughput of comparable autoregressive models at cost-optimized-tier quality. Released August 31, 2026 by Inception Labs, it is built for very high inference throughput (1,107 tok/s) via diffusion-based parallel token generation, coding accuracy (95.7%, 91st percentile among cost-optimized models), mathematics accuracy (97.0%, 97th percentile), and tunable reasoning levels with parallel tool calls and schema-aligned JSON output.
Its trade-offs: 260K context window is far shorter than frontier 1M-token models, no vision or audio modalities, positioned only against cost-optimized models (GPT-5.6 Luna Low, Gemini 3.5 Flash-Lite), not frontier-class, and current $0.04/$0.15 pricing includes a limited-time launch promotion on OpenRouter (list price is $0.20/$0.75, may rise after Sept 8, 2026). At $0.04 in / $0.15 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
Grok 4.7 and Mercury 2.5 Preview overlap enough that the right pick depends on your specific job. Mercury 2.5 Preview costs less per token; Grok 4.7 holds the larger context; and each leads in its own area — Grok 4.7 for 2.1 trillion parameters, up 40% from grok 4.6's 1.5 trillion, at the same $2/$6 per million token price, Mercury 2.5 Preview for very high inference throughput (1,107 tok/s) via diffusion-based parallel token generation. Rather than crowning one, run the same hard task through both once and let the results decide.
Want both Grok 4.7 and Mercury 2.5 Preview 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 Grok 4.7 or Mercury 2.5 Preview 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, Grok 4.7 leans toward 2.1 trillion parameters, up 40% from grok 4.6's 1.5 trillion, at the same $2/$6 per million token price while Mercury 2.5 Preview leans toward very high inference throughput (1,107 tok/s) via diffusion-based parallel token generation, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Grok 4.7 or Mercury 2.5 Preview?
Mercury 2.5 Preview is cheaper — $2/$6 per 1M tokens vs $0.04/$0.15 per 1M tokens, roughly 50× apart on input.
Which has the bigger context window?
Grok 4.7 — 500K tokens vs 260K tokens, about 1.9× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Grok 4.7 and Mercury 2.5 Preview together?
Yes — a multi-model platform like LumiChats gives you Grok 4.7, Mercury 2.5 Preview 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, Grok 4.7 or Mercury 2.5 Preview?
Grok 4.7 — released September 21, 2026, about 21 days after Mercury 2.5 Preview.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.