diff --git a/R/provider-openai.R b/R/provider-openai.R
index d6e9003c..cadb6953 100644
--- a/R/provider-openai.R
+++ b/R/provider-openai.R
@@ -49,28 +49,17 @@ chat_openai <- function(
   api_key = openai_key(),
   model = NULL,
   params = NULL,
-  seed = lifecycle::deprecated(),
   api_args = list(),
   echo = c("none", "output", "all")
 ) {
   model <- set_default(model, "gpt-4.1")
   echo <- check_echo(echo)
 
-  params <- params %||% params()
-  if (lifecycle::is_present(seed) && !is.null(seed)) {
-    lifecycle::deprecate_warn(
-      when = "0.2.0",
-      what = "chat_openai(seed)",
-      with = "chat_openai(params)"
-    )
-    params$seed <- seed
-  }
-
   provider <- ProviderOpenAI(
     name = "OpenAI",
     base_url = base_url,
     model = model,
-    params = params,
+    params = params %||% params(),
     extra_args = api_args,
     api_key = api_key
   )
@@ -84,7 +73,6 @@ chat_openai_test <- function(
   echo = "none"
 ) {
   params <- params %||% params()
-  params$seed <- params$seed %||% 1014
   params$temperature <- params$temperature %||% 0
 
   chat_openai(
@@ -145,10 +133,10 @@ method(base_request_error, ProviderOpenAI) <- function(provider, req) {
 # Chat endpoint ----------------------------------------------------------------
 
 method(chat_path, ProviderOpenAI) <- function(provider) {
-  "/chat/completions"
+  "/responses"
 }
 
-# https://platform.openai.com/docs/api-reference/chat/create
+# https://platform.openai.com/docs/api-reference/responses
 method(chat_body, ProviderOpenAI) <- function(
   provider,
   stream = TRUE,
@@ -156,33 +144,41 @@ method(chat_body, ProviderOpenAI) <- function(
   tools = list(),
   type = NULL
 ) {
-  messages <- compact(unlist(as_json(provider, turns), recursive = FALSE))
+  input <- compact(unlist(as_json(provider, turns), recursive = FALSE))
   tools <- as_json(provider, unname(tools))
 
   if (!is.null(type)) {
-    response_format <- list(
-      type = "json_schema",
-      json_schema = list(
+    # https://platform.openai.com/docs/api-reference/responses/create#responses-create-text
+    text <- list(
+      format = list(
+        type = "json_schema",
         name = "structured_data",
         schema = as_json(provider, type),
         strict = TRUE
       )
     )
   } else {
-    response_format <- NULL
+    text <- NULL
   }
 
+  # https://platform.openai.com/docs/api-reference/responses/create#responses-create-include
   params <- chat_params(provider, provider@params)
-  params$seed <- params$seed %||% provider@seed
+  if (isTRUE(params$log_probs)) {
+    include <- list("message.output_text.logprobs")
+  } else {
+    include <- NULL
+  }
+  params$log_probs <- NULL
 
   compact(list2(
-    messages = messages,
+    input = input,
+    include = include,
     model = provider@model,
     !!!params,
     stream = stream,
-    stream_options = if (stream) list(include_usage = TRUE),
     tools = tools,
-    response_format = response_format
+    text = text,
+    store = FALSE
   ))
 }
 
@@ -194,11 +190,8 @@ method(chat_params, ProviderOpenAI) <- function(provider, params) {
       temperature = "temperature",
       top_p = "top_p",
       frequency_penalty = "frequency_penalty",
-      presence_penalty = "presence_penalty",
-      seed = "seed",
-      max_tokens = "max_completion_tokens",
-      logprobs = "log_probs",
-      stop = "stop_sequences"
+      max_tokens = "max_output_tokens",
+      log_probs = "log_probs"
     )
   )
 }
@@ -213,10 +206,9 @@ method(stream_parse, ProviderOpenAI) <- function(provider, event) {
   jsonlite::parse_json(event$data)
 }
 method(stream_text, ProviderOpenAI) <- function(provider, event) {
-  if (length(event$choices) == 0) {
-    NULL
-  } else {
-    event$choices[[1]]$delta[["content"]]
+  # https://platform.openai.com/docs/api-reference/responses-streaming/response/output_text/delta
+  if (event$type == "response.output_text.delta") {
+    event$delta
   }
 }
 method(stream_merge_chunks, ProviderOpenAI) <- function(
@@ -224,56 +216,43 @@ method(stream_merge_chunks, ProviderOpenAI) <- function(
   result,
   chunk
 ) {
-  if (is.null(result)) {
-    chunk
-  } else {
-    merge_dicts(result, chunk)
+  # https://platform.openai.com/docs/api-reference/responses-streaming/response/completed
+  if (chunk$type == "response.completed") {
+    chunk$response
   }
 }
+
 method(value_turn, ProviderOpenAI) <- function(
   provider,
   result,
   has_type = FALSE
 ) {
-  if (has_name(result$choices[[1]], "delta")) {
-    # streaming
-    message <- result$choices[[1]]$delta
-  } else {
-    message <- result$choices[[1]]$message
-  }
-
-  if (has_type) {
-    if (is_string(message$content)) {
-      json <- jsonlite::parse_json(message$content[[1]])
+  contents <- lapply(result$output, function(output) {
+    if (output$type == "message") {
+      if (has_type) {
+        ContentJson(jsonlite::parse_json(output$content[[1]]$text))
+      } else {
+        ContentText(output$content[[1]]$text)
+      }
+    } else if (output$type == "function_call") {
+      arguments <- jsonlite::parse_json(output$arguments)
+      ContentToolRequest(output$id, output$name, arguments)
     } else {
-      json <- message$content
-    }
-    content <- list(ContentJson(json))
-  } else {
-    content <- lapply(message$content, as_content)
-  }
-  if (has_name(message, "tool_calls")) {
-    calls <- lapply(message$tool_calls, function(call) {
-      name <- call$`function`$name
-      # TODO: record parsing error
-      args <- tryCatch(
-        jsonlite::parse_json(call$`function`$arguments),
-        error = function(cnd) list()
+      browser()
+      cli::cli_abort(
+        "Unknown content type {.str {content$type}}.",
+        .internal = TRUE
       )
-      ContentToolRequest(name = name, arguments = args, id = call$id)
-    })
-    content <- c(content, calls)
-  }
+    }
+  })
+
+  # cached_tokens <- result$usage$input_token_details$cached_tokens
   tokens <- tokens_log(
     provider,
-    input = result$usage$prompt_tokens,
-    output = result$usage$completion_tokens
-  )
-  assistant_turn(
-    content,
-    json = result,
-    tokens = tokens
+    input = result$usage$input_tokens,
+    output = result$usage$output_tokens
   )
+  assistant_turn(contents = contents, json = result, tokens = tokens)
 }
 
 # ellmer -> OpenAI --------------------------------------------------------------
@@ -284,51 +263,42 @@ method(as_json, list(ProviderOpenAI, Turn)) <- function(provider, x) {
       list(role = "system", content = x@contents[[1]]@text)
     )
   } else if (x@role == "user") {
-    # Each tool result needs to go in its own message with role "tool"
-    is_tool <- map_lgl(x@contents, S7_inherits, ContentToolResult)
-    content <- as_json(provider, x@contents[!is_tool])
-    if (length(content) > 0) {
-      user <- list(list(role = "user", content = content))
-    } else {
-      user <- list()
-    }
-
-    tools <- lapply(x@contents[is_tool], function(tool) {
-      list(
-        role = "tool",
-        content = tool_string(tool),
-        tool_call_id = tool@request@id
-      )
+    lapply(x@contents, function(x) {
+      if (S7_inherits(x, ContentText)) {
+        list(role = "user", content = x@text)
+      } else {
+        as_json(provider, x)
+      }
     })
-
-    c(user, tools)
   } else if (x@role == "assistant") {
-    # Tool requests come out of content and go into own argument
-    is_tool <- map_lgl(x@contents, is_tool_request)
-    content <- as_json(provider, x@contents[!is_tool])
-    tool_calls <- as_json(provider, x@contents[is_tool])
-
-    list(
-      compact(list(
-        role = "assistant",
-        content = content,
-        tool_calls = tool_calls
-      ))
-    )
+    as_json(provider, x@contents)
   } else {
     cli::cli_abort("Unknown role {x@role}", .internal = TRUE)
   }
 }
 
 method(as_json, list(ProviderOpenAI, ContentText)) <- function(provider, x) {
-  list(type = "text", text = x@text)
+  # OpenAI uses a different format dependening on whether the text is provided
+  # by the user or generated by the assistant. Since ellmer content types don't
+  # distinguish, this method generates the assistant content and we special
+  # case the
+  list(
+    role = "assistant",
+    content = x@text
+  )
 }
 
 method(as_json, list(ProviderOpenAI, ContentImageRemote)) <- function(
   provider,
   x
 ) {
-  list(type = "image_url", image_url = list(url = x@url))
+  list(
+    type = "message",
+    role = "user",
+    content = list(
+      list(type = "input_image", image_url = x@url)
+    )
+  )
 }
 
 method(as_json, list(ProviderOpenAI, ContentImageInline)) <- function(
@@ -336,9 +306,13 @@ method(as_json, list(ProviderOpenAI, ContentImageInline)) <- function(
   x
 ) {
   list(
-    type = "image_url",
-    image_url = list(
-      url = paste0("data:", x@type, ";base64,", x@data)
+    type = "message",
+    role = "user",
+    content = list(
+      list(
+        type = "input_image",
+        image_url = paste0("data:", x@type, ";base64,", x@data)
+      )
     )
   )
 }
@@ -347,23 +321,32 @@ method(as_json, list(ProviderOpenAI, ContentToolRequest)) <- function(
   provider,
   x
 ) {
-  json_args <- jsonlite::toJSON(x@arguments)
   list(
-    id = x@id,
-    `function` = list(name = x@name, arguments = json_args),
-    type = "function"
+    type = "function_call",
+    call_id = x@id,
+    name = x@name,
+    arguments = jsonlite::toJSON(x@arguments)
+  )
+}
+
+method(as_json, list(ProviderOpenAI, ContentToolResult)) <- function(
+  provider,
+  x
+) {
+  list(
+    type = "function_call_output",
+    call_id = x@request@id,
+    output = tool_string(x)
   )
 }
 
 method(as_json, list(ProviderOpenAI, ToolDef)) <- function(provider, x) {
   list(
     type = "function",
-    "function" = compact(list(
-      name = x@name,
-      description = x@description,
-      strict = TRUE,
-      parameters = as_json(provider, x@arguments)
-    ))
+    name = x@name,
+    description = x@description,
+    strict = TRUE,
+    parameters = as_json(provider, x@arguments)
   )
 }
 
@@ -422,7 +405,7 @@ method(batch_submit, ProviderOpenAI) <- function(
     list(
       custom_id = paste0("chat-", i),
       method = "POST",
-      url = "/v1/chat/completions",
+      url = "/v1/responses",
       body = body
     )
   })
diff --git a/R/provider.R b/R/provider.R
index f9b3a92f..d00f6cf9 100644
--- a/R/provider.R
+++ b/R/provider.R
@@ -137,6 +137,8 @@ stream_parse <- new_generic(
     S7_dispatch()
   }
 )
+
+# Extract text that should be printed to the console
 stream_text <- new_generic(
   "stream_text",
   "provider",
diff --git a/man/chat_openai.Rd b/man/chat_openai.Rd
index 9c350270..84bfd64f 100644
--- a/man/chat_openai.Rd
+++ b/man/chat_openai.Rd
@@ -10,8 +10,7 @@ chat_openai(
   base_url = "https://api.openai.com/v1",
   api_key = openai_key(),
   model = NULL,
-  params = NULL,
-  seed = lifecycle::deprecated(),
+  params = params(),
   api_args = list(),
   echo = c("none", "output", "all")
 )
@@ -35,9 +34,6 @@ Use \code{models_openai()} to see all options.}
 
 \item{params}{Common model parameters, usually created by \code{\link[=params]{params()}}.}
 
-\item{seed}{Optional integer seed that ChatGPT uses to try and make output
-more reproducible.}
-
 \item{api_args}{Named list of arbitrary extra arguments appended to the body
 of every chat API call. Combined with the body object generated by ellmer
 with \code{\link[=modifyList]{modifyList()}}.}
@@ -51,6 +47,9 @@ when running at the console).
 }
 
 Note this only affects the \code{chat()} method.}
+
+\item{seed}{Optional integer seed that ChatGPT uses to try and make output
+more reproducible.}
 }
 \value{
 A \link{Chat} object.
diff --git a/tests/testthat/_snaps/provider-openai.md b/tests/testthat/_snaps/provider-openai.md
index 78b3be54..67b0cc15 100644
--- a/tests/testthat/_snaps/provider-openai.md
+++ b/tests/testthat/_snaps/provider-openai.md
@@ -13,12 +13,3 @@
       Error in `method(as_json, list(ellmer::ProviderOpenAI, ellmer::TypeObject))`:
       ! `.additional_properties` not supported for OpenAI.
 
-# seed is deprecated, but still honored
-
-    Code
-      chat <- chat_openai_test(seed = 1)
-    Condition
-      Warning:
-      The `seed` argument of `chat_openai()` is deprecated as of ellmer 0.2.0.
-      i Please use the `params` argument instead.
-
diff --git a/tests/testthat/_vcr/openai-v2-image.yml b/tests/testthat/_vcr/openai-v2-image.yml
new file mode 100644
index 00000000..4f4223c8
--- /dev/null
+++ b/tests/testthat/_vcr/openai-v2-image.yml
@@ -0,0 +1,192 @@
+http_interactions:
+- request:
+    method: POST
+    uri: https://api.openai.com/v1/responses
+    body:
+      string: '{"input":[{"role":"system","content":"Be terse."},{"role":"user","content":"What''s
+        in this image? (Be sure to mention the outside 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"}]}],"model":"gpt-4.1-mini","temperature":0,"stream":false}'
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+      date: Wed, 09 Jul 2025 20:13:27 GMT
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diff --git a/tests/testthat/helper-provider.R b/tests/testthat/helper-provider.R
index 84cb9a43..b352de43 100644
--- a/tests/testthat/helper-provider.R
+++ b/tests/testthat/helper-provider.R
@@ -36,15 +36,15 @@ test_tools_simple <- function(chat_fun) {
     name = "current_date",
     description = "Return the current date"
   ))
+  result <- chat$chat("What's the current date in Y-M-D format?")
+  expect_match(result, "2024-01-01")
+
   chat$register_tool(tool(
     function() "February",
     name = "current_month",
     description = "Return the full name of the current month"
   ))
 
-  result <- chat$chat("What's the current date in Y-M-D format?")
-  expect_match(result, "2024-01-01")
-
   result <- chat$chat("What month is it? Provide the full name")
   expect_match(result, "February")
 }
diff --git a/tests/testthat/test-provider-openai.R b/tests/testthat/test-provider-openai.R
index 92fe5e91..d06d27db 100644
--- a/tests/testthat/test-provider-openai.R
+++ b/tests/testthat/test-provider-openai.R
@@ -5,6 +5,9 @@ test_that("can make simple request", {
   resp <- chat$chat("What is 1 + 1?", echo = FALSE)
   expect_match(resp, "2")
   expect_equal(chat$last_turn()@tokens > 0, c(TRUE, TRUE))
+
+  resp <- chat$chat("Double that", echo = FALSE)
+  expect_match(resp, "4")
 })
 
 test_that("can make simple streaming request", {
@@ -17,21 +20,21 @@ test_that("can list models", {
   test_models(models_openai)
 })
 
-
 # Common provider interface -----------------------------------------------
 
 test_that("defaults are reported", {
   expect_snapshot(. <- chat_openai())
 })
 
-test_that("supports standard parameters", {
-  chat_fun <- chat_openai_test
+# No longer supports stop parameter
+# test_that("supports standard parameters", {
+#   chat_fun <- chat_openai_test
 
-  test_params_stop(chat_fun)
-})
+#   test_params_stop(chat_fun)
+# })
 
 test_that("supports tool calling", {
-  vcr::local_cassette("openai-tool")
+  # vcr::local_cassette("openai-v2-tool")
   chat_fun <- chat_openai_test
 
   test_tools_simple(chat_fun)
@@ -44,7 +47,7 @@ test_that("can extract data", {
 })
 
 test_that("can use images", {
-  vcr::local_cassette("openai-image")
+  # vcr::local_cassette("openai-v2-image")
   # Needs mini to get shape correct
   chat_fun <- \(...) chat_openai_test(model = "gpt-4.1-mini", ...)
 
@@ -56,13 +59,8 @@ test_that("can use images", {
 
 test_that("can retrieve log_probs (#115)", {
   chat <- chat_openai_test(params = params(log_probs = TRUE))
-  pieces <- coro::collect(chat$stream("Hi"))
-
-  logprobs <- chat$last_turn()@json$choices[[1]]$logprobs$content
-  expect_equal(
-    length(logprobs),
-    length(pieces) - 2 # leading "" + trailing \n
-  )
+  chat$chat("Hi")
+  expect_length(chat$last_turn()@json$output[[1]]$content[[1]]$logprobs, 2)
 })
 
 # Custom -----------------------------------------------------------------
@@ -87,11 +85,3 @@ test_that("as_json specialised for OpenAI", {
     )
   )
 })
-
-test_that("seed is deprecated, but still honored", {
-  expect_snapshot(chat <- chat_openai_test(seed = 1))
-  expect_equal(chat$get_provider()@params$seed, 1)
-
-  # NULL is also ignored since that's what subclasses use
-  expect_no_warning(chat_openai_test(seed = NULL))
-})