ChatGPT vs Gemini
As of October 10, 2026, GPT-6 Astra and Gemini 4 Argon have public point estimates of 84.88 at #2 and 81.87 at #6. GPT-6 Astra leads by point estimate. The conditional score ranges (79.8–89.9 and 72.1–91.6) overlap. Rank confidence has not been validated for these ranges. Gemini's top-ranked model is the cheaper one: Gemini 4 Argon at $2/$10 per million input/output tokens, against GPT-6 Astra at $10/$50. Task ranges do not establish rank confidence. Writing and visual rows are not comparable.
We compare the model rows listed below using public benchmark and API pricing evidence. The benchmark harnesses test those models under their own settings. Test the apps separately for routing, upload limits, tools and the finished work you need.
The short answer
The public ranking puts GPT-6 Astra ahead at 84.88, with Gemini 4 Argon at 81.87. The two rows sit at #2 and #6, respectively.
ChatGPT's top-ranked model is GPT-6 Astra, and its public score carries a Supported evidence label. On Terminal-Bench 4.0, GPT-6 Astra posts 57.9 against Gemini 4 Argon's 57.4. GPT-5.6 Sol posts 92.2 on BrowseComp, and neither Gemini model here has a sourced BrowseComp row.
ChatGPT's top-ranked model has the higher point estimate. Gemini's top-ranked model costs less at listed token rates. Check the category evidence and your own workloads before choosing.
Gemini vs ChatGPT by task
GPT-6 Astra and Gemini 4 Argon are the two highest-ranked model rows from the lineups above. Their task evidence is narrower than an overall score. These are model benchmarks, with app behavior and limits left for a separate test.
| Task and public lane | ChatGPT model row | Gemini model row | Basis | Reading |
|---|---|---|---|---|
| Coding | GPT-6 Astra76.1 · #4 · Supported | Gemini 4 Argon72.4 · #5 · Supported | Like-for-like | GPT-6 Astra has the higher point estimate. Conditional ranges do not establish rank confidence. |
| Agents and automation | GPT-6 Astra70.7 · #7 · Supported | Gemini 4 Argon75.3 · #4 · Estimated | Directional | Gemini 4 Argon has the higher point estimate. Conditional ranges do not establish rank confidence. |
| Research and knowledge | GPT-6 Astra86.2 · #3 · Supported | Gemini 4 Argon79.8 · #8 · Supported | Like-for-like | GPT-6 Astra has the higher point estimate. Conditional ranges do not establish rank confidence. |
| Reasoning | GPT-6 Astra93.4 · #1 | Gemini 4 ArgonNot publicly ranked | Not comparable | At least one model is not publicly ranked on this lane. No task winner is established. |
| Writing: brief adherence | GPT-6 AstraNot publicly ranked | Gemini 4 ArgonNot publicly ranked | Not comparable | At least one model is not publicly ranked on this lane. No task winner is established. |
| Images, charts and PDFs | GPT-6 AstraNot publicly ranked | Gemini 4 ArgonNot publicly ranked | Not comparable | At least one model is not publicly ranked on this lane. No task winner is established. |
Gemini vs ChatGPT for coding
GPT-6 Astra has the higher point estimate. Conditional ranges do not establish rank confidence. The coding leaderboard records benchmark tasks and their evidence. It does not measure the editor, prompt, repository access or agent you put around the model. Test the change you need made in the setup you will actually use.
At the budget end, the GPT-5.6 Luna and Gemini 3.8 Flash comparison reads: GPT-5.6 Luna has the higher point estimate. Conditional ranges do not establish rank confidence. Their listed API rates are $0.20 / $1.20 and $0.75 / $3.75 per million input/output tokens. Those are model rates, not chat subscription prices.
Gemini vs ChatGPT for writing
A brief-adherence score and a writing choice answer different questions. The instruction-following row for GPT-6 Astra and Gemini 4 Argon reads: At least one model is not publicly ranked on this lane. No task winner is established. It checks constraints represented by the benchmark, rather than whether a draft fits your reader, sounds right or makes a useful argument.
Compare one real brief, its source material and the same review criteria in both apps. Check factual support, tone and the edits needed to accept the draft. A general human-preference rating is a reason to inspect examples, with its uncertainty intact. It does not turn the missing writing evaluation into a measured winner.
Gemini vs ChatGPT for research and long documents
For GPT-6 Astra and Gemini 4 Argon, the knowledge reading is: GPT-6 Astra has the higher point estimate. Conditional ranges do not establish rank confidence. The reasoning reading is: At least one model is not publicly ranked on this lane. No task winner is established. Knowledge questions and reasoning tasks can screen a model. They do not establish whether a research answer uses the right document or whether its citations support the claim.
The budget knowledge rows for GPT-5.6 Luna and Gemini 3.8 Flash read: Gemini 3.8 Flash has the higher point estimate. Conditional ranges do not establish rank confidence. For document work, try a question answered deep in a file, a question the file cannot answer and two conflicting passages. A listed context allowance is an input limit. Test retrieval, citation support and the app's actual upload limits separately.
Gemini vs ChatGPT for images, charts and PDFs
The current visual-understanding row for GPT-6 Astra and Gemini 4 Argon reads: At least one model is not publicly ranked on this lane. No task winner is established. A missing public rank is a coverage limit. It does not show that a model failed every visual task or cannot read your file.
Older measured rows provide context: GPT-5.6 Sol against Gemini 3.1 Pro reads: GPT-5.6 Sol scores higher, with Estimated evidence or a different benchmark basis. No task winner is established. Those are different models. For the app you intend to use, check a chart's units, a scanned page and a PDF question against their source. The multimodal evidence concerns understanding; it does not compare generated images or videos.
ChatGPT vs Gemini: model evidence
These are the model rows included in this comparison. Public scores and ranks come from the main leaderboard lane; the preference column is a human-preference rating from an independent index, shown where one is published.
| Model | Score | Preference rating | Context |
|---|---|---|---|
| GPT-6 AstraOpenAI | 84.88 | 1477.1 | 1.05M |
| GPT-5.6 SolOpenAI | 77.81 | 1483.9 | 1.05M |
| GPT-5.6 TerraOpenAI | 72.34 | 1465.5 | 1.05M |
| GPT-5.6 LunaOpenAI | 66.15 | 1453.0 | 1.05M |
| Gemini 4 ArgonGoogle | 81.87 | 1525.2 | — |
| Gemini 3.8 FlashGoogle | 73.17 | 1494.8 | 1M |
| Gemini 3.1 ProGoogle | 65.17 | 1487.0 | 1M |
Google's Gemini 4 Argon announcement limits its rollout to trusted cyber defenders through the Fairwind Program. Its ranking row does not establish access in the Gemini app. Check the model and plan available to you before using either lineup as a shortlist.
For the benchmark-by-benchmark detail, see the dedicated model pages: Gemini 4 Argon vs GPT-6 Astra for the top-ranked matchup, or Gemini 3.1 Pro vs GPT-5.6 Sol for Google's Pro model against the GPT-5.6 flagship.
ChatGPT vs Gemini pricing: subscriptions and API
Check each chat subscription's current plan terms before comparing monthly costs and included features. The API table below prices token usage. It does not quote a monthly app subscription or establish which plan includes a listed model.
The listed API rates use the same unit; access, context tiers, caching, and tool charges can change your bill. At the top of the ranking, Gemini 4 Argon lists at $2 / $10 per million input / output tokens against $10 / $50 for GPT-6 Astra. At the budget tier the order flips: GPT-5.6 Luna ($0.20 / $1.20) undercuts Gemini 3.8 Flash ($0.75 / $3.75). Full rate cards live on the OpenAI API pricing and Google API pricing hubs.
| Model | Input / 1M tokens | Output / 1M tokens | Note |
|---|---|---|---|
| GPT-6 Astra | $10.00 | $50.00 | — |
| GPT-5.6 Sol | $4.00 | $20.00 | Promotional rate, at least through Nov 21, 2026 |
| GPT-5.6 Terra | $2.00 | $12.00 | — |
| GPT-5.6 Luna | $0.20 | $1.20 | — |
| Gemini 4 Argon | $2.00 | $10.00 | Restricted access; introductory launch rate, no end date announced |
| Gemini 3.8 Flash | $0.75 | $3.75 | Introductory rate through Dec 31, 2026; $1.50 / $7.50 after |
| Gemini 3.1 Pro | $2.00 | $12.00 | Rises to $4 / $18 above 200K-token prompts |
Which should you pick?
Pick ChatGPT if…
- You want the higher public score: GPT-6 Astra posts 84.88, versus 81.87 for Gemini 4 Argon.
- Agentic and terminal work is the job: GPT-6 Astra posts 57.9 on Terminal-Bench 4.0 against 57.4 for Gemini 4 Argon.
- You lean on web-research agents: GPT-5.6 Sol posts 92.2 on BrowseComp, where no Gemini model here has a sourced row.
Pick Gemini if…
- Price matters at the top end: $2 / $10 per million tokens for Gemini 4 Argon versus $10 / $50 for GPT-6 Astra.
- You want to test Gemini 4 Argon on your own work: its public overall score is 81.87 at #6.
- Human preference is your proxy for quality: Gemini 4 Argon's 1525.2 human-preference rating is the highest published for any model on this page.
How this comparison works
We compare the listed model rows as evidence for a shortlist. App routing, plans, and tools need their own workload test. Overall scores use the current public ranking lane; preference ratings come from an independent human-preference index and appear only where one has been published; API prices come from each provider's official rate card as recorded in BenchLM's pricing data. Models outside the public ranking show as unranked instead of receiving a legacy score. Every individual benchmark quoted in the text comes from the same sourced dataset that powers our model comparison pages.
Questions
Is Gemini better than ChatGPT?
Not on the current public score. GPT-6 Astra scores 84.88 at #2, while Gemini 4 Argon scores 81.87 at #6. GPT-6 Astra's position carries a Supported evidence label. Gemini can still be the better purchase when lower API pricing matters more than the point-score lead.
Is Gemini cheaper than ChatGPT?
Only at the top of each lineup. Gemini 4 Argon, Google's best-ranked model here, costs $12 per million input plus output tokens against $60 for GPT-6 Astra, while GPT-5.6 Luna, at $1.40, is the cheapest model on the page. Those are listed API rates. Compare the current chat plan terms separately for a monthly subscription.
Which is better for coding, ChatGPT or Gemini?
ChatGPT, on the public coding ranking: GPT-6 Astra ranks #4 at 76.11, against Gemini 4 Argon at #5 with 72.41. GPT-6 Astra leads by point estimate; its evidence label is Supported. The conditional ranges do not establish rank confidence. GPT-6 Astra also leads Terminal-Bench 4.0, 57.9 to 57.4. At the budget end, GPT-5.6 Luna ($0.20 / $1.20) lists below Gemini 3.8 Flash and still ranks #13 on coding.
Can I use both ChatGPT and Gemini?
If both apps are available to you, compare the same task in each. Keep the source material, acceptance criteria and review process consistent. Choose by the work you can accept and the total cost in your actual setup.